sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
0.99
|
|---|---|---|
1. A computer-implemented method for providing a definition or a translation, comprising: receiving an input indicating a word selected by a user; determining a user's language; communicating the determined user's language to a definition server and a translation server; sending, simultaneously, a definition request for the word to the definition server along with sending a translation request for the word to the translation server; receiving a response to the definition request from the definition server, wherein the response to the definition request indicates whether there is at least one definition of the word in the user's language; receiving a response to the translation request from the translation server, wherein the response to the translation request indicates whether there is at least one translation of the word in the user's language, wherein the response to the definition request and the response to the translation request are received simultaneously; determining whether to provide the user with a definition or a translation of the word based on the responses from the definition server and the translation server, wherein the determination comprises: determining to provide the user with the definition of the word when the response to the definition request includes at least one definition of the word in the user's language; and determining to provide the user with the translation of the word when the response to the definition request indicates that there is no definition of the word in the user's language and the response to the translation request includes at least one translation of the word in the user's language; and providing the user with the definition or the translation of the word based on the determination of whether to provide the user with a definition or a translation of the word, wherein the providing comprises a bubble showing the at least one definition or the at least one translation of the selected word.
|
1. A computer-implemented method for providing a definition or a translation, comprising: receiving an input indicating a word selected by a user; determining a user's language; communicating the determined user's language to a definition server and a translation server; sending, simultaneously, a definition request for the word to the definition server along with sending a translation request for the word to the translation server; receiving a response to the definition request from the definition server, wherein the response to the definition request indicates whether there is at least one definition of the word in the user's language; receiving a response to the translation request from the translation server, wherein the response to the translation request indicates whether there is at least one translation of the word in the user's language, wherein the response to the definition request and the response to the translation request are received simultaneously; determining whether to provide the user with a definition or a translation of the word based on the responses from the definition server and the translation server, wherein the determination comprises: determining to provide the user with the definition of the word when the response to the definition request includes at least one definition of the word in the user's language; and determining to provide the user with the translation of the word when the response to the definition request indicates that there is no definition of the word in the user's language and the response to the translation request includes at least one translation of the word in the user's language; and providing the user with the definition or the translation of the word based on the determination of whether to provide the user with a definition or a translation of the word, wherein the providing comprises a bubble showing the at least one definition or the at least one translation of the selected word. 3. The method of claim 1 , wherein determining whether to provide the user with a definition or a translation of the word comprises determining to provide the user with the definition of the word when the response to the definition request includes at least one definition of the word in the user's language, and the response to the translation request indicates a detected source language of the word matching the user's language.
| 0.576776 |
11. A method comprising: determining at least one spammer targeted keyword relating to a common keyword used in commerce search queries, the determining being based in part on a popularity of the at least one spammer targeted keyword amongst advertisers, wherein the popularity of the at least one spammer targeted keyword amongst the advertisers is based in part on a number of bids provided by the advertisers, and wherein the at least one spammer targeted keyword is associated with a syndication business, the syndication business including at least a publisher, an advertiser, and a syndicator; inputting the at least one spammer targeted keyword to a search engine to generate search results including a plurality of uniform resource locators (URLs); accessing, by one or more processors, one or more URLs of the plurality of URLs; recording the one or more URLs, wherein the recording comprises redirection tracking that intercepts redirection traffic; grouping the one or more recorded URLs using similarity-based grouping; verifying that at least one of the one or more URLs comprises a spam URL; and determining that the spam URL is associated with a spam syndication program, the spam syndication program including at least a spam publisher associated with a doorway page for redirecting a browser to a redirection domain associated with the spam publisher.
|
11. A method comprising: determining at least one spammer targeted keyword relating to a common keyword used in commerce search queries, the determining being based in part on a popularity of the at least one spammer targeted keyword amongst advertisers, wherein the popularity of the at least one spammer targeted keyword amongst the advertisers is based in part on a number of bids provided by the advertisers, and wherein the at least one spammer targeted keyword is associated with a syndication business, the syndication business including at least a publisher, an advertiser, and a syndicator; inputting the at least one spammer targeted keyword to a search engine to generate search results including a plurality of uniform resource locators (URLs); accessing, by one or more processors, one or more URLs of the plurality of URLs; recording the one or more URLs, wherein the recording comprises redirection tracking that intercepts redirection traffic; grouping the one or more recorded URLs using similarity-based grouping; verifying that at least one of the one or more URLs comprises a spam URL; and determining that the spam URL is associated with a spam syndication program, the spam syndication program including at least a spam publisher associated with a doorway page for redirecting a browser to a redirection domain associated with the spam publisher. 15. The method of claim 11 , wherein the grouping comprises grouping at least one of the one or more recorded URLs with a preexisting group.
| 0.675352 |
9. A computer readable storage medium tangibly embodying program instructions which, when executed by a computer, implement a method for incorporating at least user-supplied text into an electronic product design having a first content area containing one or more content elements, the method comprising receiving a plurality of user text entries, the plurality of text entries comprising at least one text entry being of a first horizontal alignment type and at least one text entry being of a second horizontal alignment type, determining a first height, the first height being the height of all received text entries of the first horizontal alignment type positioned in a vertical arrangement, and a second height, the second height being the height of all received text entries of the second horizontal alignment type positioned in a vertical arrangement, modifying the electronic product design by sizing a second content area outside the first content area according to the larger of the first and second heights, positioning the plurality of user text entries in the product design in the second content area, and resizing the first content area to accommodate the second content area in the electronic product design, determining an available text width in the second content area, partitioning the available text width into a first maximum justified text width and a second maximum justified text width, and justifying the one or more user text entries of the first horizontal alignment type according to the first horizontal alignment type, wrapping such text entries as exceed the first maximum justified text width, and justifying the one or more user text entries of the second horizontal alignment type according to the second horizontal alignment type, wrapping such text entries as exceed the second maximum justified text width.
|
9. A computer readable storage medium tangibly embodying program instructions which, when executed by a computer, implement a method for incorporating at least user-supplied text into an electronic product design having a first content area containing one or more content elements, the method comprising receiving a plurality of user text entries, the plurality of text entries comprising at least one text entry being of a first horizontal alignment type and at least one text entry being of a second horizontal alignment type, determining a first height, the first height being the height of all received text entries of the first horizontal alignment type positioned in a vertical arrangement, and a second height, the second height being the height of all received text entries of the second horizontal alignment type positioned in a vertical arrangement, modifying the electronic product design by sizing a second content area outside the first content area according to the larger of the first and second heights, positioning the plurality of user text entries in the product design in the second content area, and resizing the first content area to accommodate the second content area in the electronic product design, determining an available text width in the second content area, partitioning the available text width into a first maximum justified text width and a second maximum justified text width, and justifying the one or more user text entries of the first horizontal alignment type according to the first horizontal alignment type, wrapping such text entries as exceed the first maximum justified text width, and justifying the one or more user text entries of the second horizontal alignment type according to the second horizontal alignment type, wrapping such text entries as exceed the second maximum justified text width. 10. The computer readable storage medium of claim 9 wherein the first horizontal alignment type is text to be positioned in a first position relative to the second content area and the second horizontal alignment type is text to be positioned in a second position relative to the second content area.
| 0.602167 |
1. A method of generating an additional information-added document of an image forming apparatus including at least one document box, the method comprising: receiving a property of the additional information of each of the at least one document box in the image forming apparatus; storing a first document, which is an object document, to one of the at least one document box according to a property of the first document; generating a second document by inserting additional information corresponding to a property that is set in the document box in which the first document is stored, to the first document; and storing the second document.
|
1. A method of generating an additional information-added document of an image forming apparatus including at least one document box, the method comprising: receiving a property of the additional information of each of the at least one document box in the image forming apparatus; storing a first document, which is an object document, to one of the at least one document box according to a property of the first document; generating a second document by inserting additional information corresponding to a property that is set in the document box in which the first document is stored, to the first document; and storing the second document. 2. The method of claim 1 , wherein at least one of the group consisting of the generated second document and the stored second document is transmitted to at least one receiving device according to a preset manipulation.
| 0.723797 |
22. The system of claim 21 , wherein the modification component dynamically modifies the source code at least in part by one or more of the following: tagging the set of keywords using a markup language to designate the keywords; using the markup language to designate the event triggers; or using the markup language to designate the actions.
|
22. The system of claim 21 , wherein the modification component dynamically modifies the source code at least in part by one or more of the following: tagging the set of keywords using a markup language to designate the keywords; using the markup language to designate the event triggers; or using the markup language to designate the actions. 23. The system of claim 22 , wherein each of the set of keywords can be any word of the web page.
| 0.914778 |
1. A non-transitory computer-readable medium comprising computer instructions embodied therein, wherein the computer instructions, when executed by at least one computing device, configure the at least one computing device to perform actions comprising: selecting a user from a plurality of users in a social network of a target user; scanning metadata associated with content items shared by the selected user; determining a list of keywords associated with the content items based on the metadata; accessing social network data associated with the selected user, the social network data including a relationship classifier that classifies a relationship between the selected user and the target user and a social network distance between the target user and the selected user, and a trust classifier that classifies a trust level between the selected user and the target user; determining a plurality of keyword scores based on the social network data, each of the plurality of keyword scores corresponding to one of the keywords on the list of keywords, wherein each of the plurality of scores is weighted by the trust classifier and an adjustment factor inversely proportional to the social network distance; normalizing individual keyword scores of the plurality of keywords scores based on a number of the content items shared by the selected user in comparison to a number of content items shared by other selected users of the plurality of users when the number of the content items shared by the selected user is greater than the number of content items shared by other selected users of the plurality of users; and generating a profile for the target user, the profile having the list of keywords and the corresponding plurality of keyword scores based on the scoring of each keyword.
|
1. A non-transitory computer-readable medium comprising computer instructions embodied therein, wherein the computer instructions, when executed by at least one computing device, configure the at least one computing device to perform actions comprising: selecting a user from a plurality of users in a social network of a target user; scanning metadata associated with content items shared by the selected user; determining a list of keywords associated with the content items based on the metadata; accessing social network data associated with the selected user, the social network data including a relationship classifier that classifies a relationship between the selected user and the target user and a social network distance between the target user and the selected user, and a trust classifier that classifies a trust level between the selected user and the target user; determining a plurality of keyword scores based on the social network data, each of the plurality of keyword scores corresponding to one of the keywords on the list of keywords, wherein each of the plurality of scores is weighted by the trust classifier and an adjustment factor inversely proportional to the social network distance; normalizing individual keyword scores of the plurality of keywords scores based on a number of the content items shared by the selected user in comparison to a number of content items shared by other selected users of the plurality of users when the number of the content items shared by the selected user is greater than the number of content items shared by other selected users of the plurality of users; and generating a profile for the target user, the profile having the list of keywords and the corresponding plurality of keyword scores based on the scoring of each keyword. 3. The non-transitory computer-readable medium as set forth in claim 1 , wherein accessing the social network data includes interfacing with at least one social network computing device and obtaining the social network data associated with the selected user.
| 0.562588 |
30. The method of claim 29 , wherein the first client content version of the sourced document is an HTML (Hypertext Markup Language) document and the path tag set for the first partially distinguished word in the first client content version is the same as the path tag set for the undistinguished word in the first client content version.
|
30. The method of claim 29 , wherein the first client content version of the sourced document is an HTML (Hypertext Markup Language) document and the path tag set for the first partially distinguished word in the first client content version is the same as the path tag set for the undistinguished word in the first client content version. 31. The method of claim 30 , wherein the path tag sequence for the first partially distinguished word in the first client content version is the same as the path tag sequence for the undistinguished word in the first client content version.
| 0.922465 |
1. A method for managing data related to network elements in a telecommunications network, comprising: receiving, at a server, a document containing data related to one or more network elements in the telecommunications network, the document associated with a corresponding source provider, a location, a receipt timestamp indicating the time and date that the document was received, and a creation timestamp indicating the time and date that the document was created; determining a document class for the document; generating an intermediate, in-memory representation of the document data, the intermediate representation comprising a plurality of key-value pairs, wherein each key-value pair is associated with a network element in the telecommunications network; identifying a parsing template corresponding to the document class and the corresponding source provider of the document, the parsing template comprising a plurality of parsing rules; parsing the intermediate representation according to the plurality of parsing rules to identify relevant values from the intermediate representation; correlating the identified values to a network model according to the plurality of parsing rules, the network model comprising a plurality of network entities that represent types of network elements in the telecommunications network, wherein the network model provides a uniform structure to be applied across a plurality of source providers, wherein each network entity of the network model comprises one or more attributes, and wherein each identified value is correlated to an attribute of a network entity in the network model based on a respective parsing rule of the parsing template; normalizing each identified value according to a format defined by the network model; writing the normalized values to a networking database, the networking database comprising a plurality of different types of data related to network elements in the telecommunications network, wherein the written values are linked to the corresponding associated network elements and correlated network entity attributes.
|
1. A method for managing data related to network elements in a telecommunications network, comprising: receiving, at a server, a document containing data related to one or more network elements in the telecommunications network, the document associated with a corresponding source provider, a location, a receipt timestamp indicating the time and date that the document was received, and a creation timestamp indicating the time and date that the document was created; determining a document class for the document; generating an intermediate, in-memory representation of the document data, the intermediate representation comprising a plurality of key-value pairs, wherein each key-value pair is associated with a network element in the telecommunications network; identifying a parsing template corresponding to the document class and the corresponding source provider of the document, the parsing template comprising a plurality of parsing rules; parsing the intermediate representation according to the plurality of parsing rules to identify relevant values from the intermediate representation; correlating the identified values to a network model according to the plurality of parsing rules, the network model comprising a plurality of network entities that represent types of network elements in the telecommunications network, wherein the network model provides a uniform structure to be applied across a plurality of source providers, wherein each network entity of the network model comprises one or more attributes, and wherein each identified value is correlated to an attribute of a network entity in the network model based on a respective parsing rule of the parsing template; normalizing each identified value according to a format defined by the network model; writing the normalized values to a networking database, the networking database comprising a plurality of different types of data related to network elements in the telecommunications network, wherein the written values are linked to the corresponding associated network elements and correlated network entity attributes. 29. The method of claim 1 , wherein the data values within the networking database are immutable and are correlated to a determined time period.
| 0.580537 |
24. The RTVMM of claim 12 wherein the implementing step comprises the steps: partitioning memory into at least three demi-spaces, at least one of the demi-spaces being a static space excluded from the garbage collection process; designating two of the demi-spaces as to-space and from-space at the beginning of a garbage collection cycle, live objects residing in from-space subsequently being copied into to-space; designating the remaining demi-spaces as mark-and-sweep spaces at the beginning of a garbage collection cycle, the mark-and-sweep spaces being garbage collected using a mark-and-sweep technique.
|
24. The RTVMM of claim 12 wherein the implementing step comprises the steps: partitioning memory into at least three demi-spaces, at least one of the demi-spaces being a static space excluded from the garbage collection process; designating two of the demi-spaces as to-space and from-space at the beginning of a garbage collection cycle, live objects residing in from-space subsequently being copied into to-space; designating the remaining demi-spaces as mark-and-sweep spaces at the beginning of a garbage collection cycle, the mark-and-sweep spaces being garbage collected using a mark-and-sweep technique. 30. The RTVMM of claim 24 wherein the implementing step comprises the step: including a "scan list" field for each object in memory, the "scan list" field distinguishing marked and unmarked objects residing in a mark-and-sweep space but not on a free list, the "scan list" field for each object in a mark-and-sweep space having a "scan clear" value at the beginning of a garbage collection cycle, an object recognized as being a live object being placed on a list of recognized live objects, the "scan list" field for an object on the list of recognized live objects having either a "scan end" value denoting the last object on the list of recognized live objects or a value identifying the next object on the list of recognized live objects, the "scan list" field for an object residing on a free list within a mark-and-sweep space or to- space having the "scan free" value, the "scan list" field for an object residing in from-space which has been scheduled for copying into to-space being a pointer to the to-space copy, the "scan list" field otherwise being assigned the "scan clear" value, the "scan list" field for an object residing in to-space having the "scan clear" value at the beginning of a garbage collection cycle, a to-space object recognized as live during garbage collection being placed on a list of recognized live objects, the "scan list" field for a to-space object on the list of recognized live objects having a value identifying the next object on the list of recognized live objects, the "scan list" field for each object queued for copying into to-space having the "scan end" value denoting that the object is live.
| 0.557676 |
1. A user-interface method for searching a relatively large set of content items in response to unresolved keystroke entry by a user from a keypad with overloaded keys in which a given key is in fixed association with a plurality of alphabetical and numerical symbols and the entry has relatively few keystrokes so that a subset of targeted content item results is quickly presented, the method comprising: using an ordering criteria to rank and associate subsets of content items with corresponding strings of one or more unresolved keystrokes for overloaded keys so that the subsets of content items are directly mapped to the corresponding strings of unresolved keystrokes; subsequent to ranking and associating the content items with strings of unresolved keystrokes, receiving a first unresolved keystroke from a user, wherein one of the plurality of alphabetical and numerical symbols in fixed association with the first unresolved keystroke is a symbol the user is using to search for desired content items; selecting and presenting the subset of content items that is associated with the first unresolved keystroke based on the direct mapping of unresolved keystrokes to the subsets of content items; subsequent to receiving the first unresolved keystroke, receiving subsequent unresolved keystrokes from the user and forming a string of unresolved keystrokes including the first unresolved keystroke and the subsequent unresolved keystrokes in the order received; an selecting and presenting the subset of content items that is associated with the string of unresolved keystrokes received based on the direct mapping of unresolved keystrokes to the subsets of content items; wherein at least one of selecting the subset of content items associated with the first unresolved keystroke and selecting the subset of content items associated with the string of unresolved keystrokes is performed using a data structure or a term intersection process or a combination thereof, the data structure including a first storage structure and a second storage structure, the first storage structure including a plurality of subsets of content items, each subset being associated with a corresponding string of unresolved keystrokes, wherein using the data structure to select a subset of content items includes returning the subset of content items of the first storage structure that is associated with the string of unresolved keystrokes entered by the user and retrieving additional content items from the second storage structure if the desired content items are not present in the first storage structure.
|
1. A user-interface method for searching a relatively large set of content items in response to unresolved keystroke entry by a user from a keypad with overloaded keys in which a given key is in fixed association with a plurality of alphabetical and numerical symbols and the entry has relatively few keystrokes so that a subset of targeted content item results is quickly presented, the method comprising: using an ordering criteria to rank and associate subsets of content items with corresponding strings of one or more unresolved keystrokes for overloaded keys so that the subsets of content items are directly mapped to the corresponding strings of unresolved keystrokes; subsequent to ranking and associating the content items with strings of unresolved keystrokes, receiving a first unresolved keystroke from a user, wherein one of the plurality of alphabetical and numerical symbols in fixed association with the first unresolved keystroke is a symbol the user is using to search for desired content items; selecting and presenting the subset of content items that is associated with the first unresolved keystroke based on the direct mapping of unresolved keystrokes to the subsets of content items; subsequent to receiving the first unresolved keystroke, receiving subsequent unresolved keystrokes from the user and forming a string of unresolved keystrokes including the first unresolved keystroke and the subsequent unresolved keystrokes in the order received; an selecting and presenting the subset of content items that is associated with the string of unresolved keystrokes received based on the direct mapping of unresolved keystrokes to the subsets of content items; wherein at least one of selecting the subset of content items associated with the first unresolved keystroke and selecting the subset of content items associated with the string of unresolved keystrokes is performed using a data structure or a term intersection process or a combination thereof, the data structure including a first storage structure and a second storage structure, the first storage structure including a plurality of subsets of content items, each subset being associated with a corresponding string of unresolved keystrokes, wherein using the data structure to select a subset of content items includes returning the subset of content items of the first storage structure that is associated with the string of unresolved keystrokes entered by the user and retrieving additional content items from the second storage structure if the desired content items are not present in the first storage structure. 3. The method of claim 1 wherein associating subsets of content items with corresponding strings of unresolved keystrokes comprises indexing said content items by performing a many-to-many mapping of descriptors associated with said content items to unresolved keystroke strings corresponding to various search query prefix substrings.
| 0.541979 |
1. In a computing environment, a method performed at least in part on at least one processor, comprising: receiving, by a speech recognition system, spoken utterances and associated confirmations; processing, by a classifier of the speech recognition system, the spoken utterances and associated confirmations from output data associated with the speech recognition system, including for each spoken utterance having a denied confirmation, assigning a pseudo-semantic label that is a representation of an association between the denied confirmation and a rejected semantic label selected from a set of potential semantic labels, and updating a classification model associated with the classifier using each assigned pseudo-semantic label, wherein the denied confirmation comprises determining a negative response to a confirmation prompt delivered by the speech recognition system.
|
1. In a computing environment, a method performed at least in part on at least one processor, comprising: receiving, by a speech recognition system, spoken utterances and associated confirmations; processing, by a classifier of the speech recognition system, the spoken utterances and associated confirmations from output data associated with the speech recognition system, including for each spoken utterance having a denied confirmation, assigning a pseudo-semantic label that is a representation of an association between the denied confirmation and a rejected semantic label selected from a set of potential semantic labels, and updating a classification model associated with the classifier using each assigned pseudo-semantic label, wherein the denied confirmation comprises determining a negative response to a confirmation prompt delivered by the speech recognition system. 9. The method of claim 1 further comprising: performing the step of assigning the pseudo-semantic label and the step of updating the classification model for another training iteration.
| 0.666538 |
3. The method of claim 2 wherein the field for which data is to be entered is displayed at a first location and the method includes: creating a new field at a second location.
|
3. The method of claim 2 wherein the field for which data is to be entered is displayed at a first location and the method includes: creating a new field at a second location. 4. The method of claim 3 wherein the creating step includes entering an alpha character at the second location.
| 0.894231 |
13. The system of claim 12 , wherein each of the plurality of categories is associated with respective sets of one or more keywords such that the first category is associated with one or more keywords that describe items in the first category.
|
13. The system of claim 12 , wherein each of the plurality of categories is associated with respective sets of one or more keywords such that the first category is associated with one or more keywords that describe items in the first category. 14. The system of claim 13 , wherein to determine that the item belongs to the first category, the one or more physical processors are further programmed to cause the computer to: compare the keyword with the respective sets of one or more keywords associated with each of the plurality of categories; determine a perfect or imperfect match between the keyword and at least one of the keywords from the respective sets of one or more keywords, wherein the item is determined to belong to the first category based on the perfect or imperfect match.
| 0.854534 |
1. A computer-implemented method of analyzing a document with a managed research domain, comprising: parsing text of a first document to identify one or more assertions made by the text of the first document, wherein each assertion comprises one or more premises and at least one conclusion; for each identified assertion: generating assertion metadata describing a relationship between one or more topics in the assertion, wherein the assertion metadata further comprises a measure of strength of the identified assertion, and determining a set of documents stored by the managed research domain that contain assertions regarding the topics identified in the assertion; and providing an indication to a user of the set of documents that contain assertions regarding the topics identified in the one or more assertions.
|
1. A computer-implemented method of analyzing a document with a managed research domain, comprising: parsing text of a first document to identify one or more assertions made by the text of the first document, wherein each assertion comprises one or more premises and at least one conclusion; for each identified assertion: generating assertion metadata describing a relationship between one or more topics in the assertion, wherein the assertion metadata further comprises a measure of strength of the identified assertion, and determining a set of documents stored by the managed research domain that contain assertions regarding the topics identified in the assertion; and providing an indication to a user of the set of documents that contain assertions regarding the topics identified in the one or more assertions. 7. The computer-implemented method of claim 1 , wherein the indication provides a prevalence of assertion strengths made by a first topic and a second topic identified in the assertion.
| 0.538908 |
12. A system, comprising: a processing device; a network interface; non-transitory computer readable memory storing program code that when executed by the processing device is configured to cause the system to at least: provide a software program for download to a first computing device associated with a user; enable delivery of a voice message, directed to the user, to the first computing device associated with the user, wherein the delivered voice message is playable to the user via a user interface of the software program; enable the voice message to be played via a web browser of a second computing device associated with the user; enable the user to send a textual reply message, via the web browser of the second computing device associated with the user, to an originator of the voice message without the user entering an address of the originator of the voice message: receive, via the network interface, a user voice message deletion instruction from the web browser of the second computing device associated with the user; and in response to the user voice message deletion instruction received from the web browser of the second computing device associated with the user, enable, in cooperation with the software program on the first computing device associated with of the user, deletion of the voice message on the first computing device associated with the user.
|
12. A system, comprising: a processing device; a network interface; non-transitory computer readable memory storing program code that when executed by the processing device is configured to cause the system to at least: provide a software program for download to a first computing device associated with a user; enable delivery of a voice message, directed to the user, to the first computing device associated with the user, wherein the delivered voice message is playable to the user via a user interface of the software program; enable the voice message to be played via a web browser of a second computing device associated with the user; enable the user to send a textual reply message, via the web browser of the second computing device associated with the user, to an originator of the voice message without the user entering an address of the originator of the voice message: receive, via the network interface, a user voice message deletion instruction from the web browser of the second computing device associated with the user; and in response to the user voice message deletion instruction received from the web browser of the second computing device associated with the user, enable, in cooperation with the software program on the first computing device associated with of the user, deletion of the voice message on the first computing device associated with the user. 25. The system as defined in claim 12 , wherein the system is further configured to: receive via the network interface a presence indication transmission from the software program hosted on the first computing device associated with the user, the presence indication transmission indicating that the first computing device associated with the user is online.
| 0.661959 |
1. A user-interface system for entering an alphanumeric string, the system comprising: presentation logic for displaying on a presentation device an alphabet arranged into a row of letters, the presentation logic including logic to display a string field for presenting an alphanumeric string of characters selected by a user; indication logic, cooperative with the presentation logic, for presenting visual cues grouping a series of letters of the row into a cluster of letters to aid in the navigation of the row and the selection of a desired cluster; navigation logic, cooperative with the indication logic, for receiving user actions from an input device to move the visual cues along the row of letters to change the letters grouped into the cluster from a first subset of letters to a second subset of letters, the visual cues moving along the row of letters in variable offsets based on a rate of input of the user actions, wherein the visual cues move by a single offset for each user action in response to user actions entered at or slower than a predetermined rate, and wherein the visual cues move by more than a single offset for each user action and the first subset of letters and the second subset of letters are contiguous in response to user actions entered faster than the predetermined rate; and selection logic for receiving user actions from the input device to select the cluster of letters to cause at least one of the letters of the selected cluster to be displayed in the string field.
|
1. A user-interface system for entering an alphanumeric string, the system comprising: presentation logic for displaying on a presentation device an alphabet arranged into a row of letters, the presentation logic including logic to display a string field for presenting an alphanumeric string of characters selected by a user; indication logic, cooperative with the presentation logic, for presenting visual cues grouping a series of letters of the row into a cluster of letters to aid in the navigation of the row and the selection of a desired cluster; navigation logic, cooperative with the indication logic, for receiving user actions from an input device to move the visual cues along the row of letters to change the letters grouped into the cluster from a first subset of letters to a second subset of letters, the visual cues moving along the row of letters in variable offsets based on a rate of input of the user actions, wherein the visual cues move by a single offset for each user action in response to user actions entered at or slower than a predetermined rate, and wherein the visual cues move by more than a single offset for each user action and the first subset of letters and the second subset of letters are contiguous in response to user actions entered faster than the predetermined rate; and selection logic for receiving user actions from the input device to select the cluster of letters to cause at least one of the letters of the selected cluster to be displayed in the string field. 9. The system of claim 1 , further comprising logic, cooperative with the presentation logic, for displaying a row of numerals adjacent to the row of letters.
| 0.544872 |
7. A computer system comprising: an input-output interface; a processor; and a memory system coupled to the processor and to the input-output interface and encoded with instructions implementing a called method and one or more nested calling methods, the called and calling methods collectively providing a normal flow of instructions for obtaining a normal processing result, the normal processing result being the first of a plurality of processing results, such that the called and calling methods, when performed on the processor, cause the computer system to perform the operations of: establishing distinct first and second exception object types; in the called method, (i) performing an expected function within the normal flow of instructions, (ii) determining if a first result condition exists, and if so then generating a first exception object as an instance of the first exception object type, the first exception object containing the normal processing result, the generating of the first exception object resulting in a return to an immediately preceding one of the calling methods, and (iii) determining if a second result condition distinct from the first result condition exists, and if so then generating second exception object of the second exception object type, the second exception object containing a second of the processing results, the generating of the second exception object resulting in a return to the immediately preceding calling method; and among the one or more calling methods, (i) calling the called method, (ii) in either the immediately preceding calling method or a higher level calling method: (iia) determining whether an object of the first exception object type has been generated by the called method, and if so then processing the normal processing result from the first exception object, and (iib) determining whether an object of the second exception object type has been generated by the called method, and if so then processing the second processing result from the second exception object; wherein the immediately preceding calling method is operative to: (i) determine whether an object of the first exception object type has been generated by the called method, and if so then process the normal processing result from the first exception object, and (ii) determine whether an object of the second exception object type has been generated by the called method, and if so then process the second processing result from the second exception object.
|
7. A computer system comprising: an input-output interface; a processor; and a memory system coupled to the processor and to the input-output interface and encoded with instructions implementing a called method and one or more nested calling methods, the called and calling methods collectively providing a normal flow of instructions for obtaining a normal processing result, the normal processing result being the first of a plurality of processing results, such that the called and calling methods, when performed on the processor, cause the computer system to perform the operations of: establishing distinct first and second exception object types; in the called method, (i) performing an expected function within the normal flow of instructions, (ii) determining if a first result condition exists, and if so then generating a first exception object as an instance of the first exception object type, the first exception object containing the normal processing result, the generating of the first exception object resulting in a return to an immediately preceding one of the calling methods, and (iii) determining if a second result condition distinct from the first result condition exists, and if so then generating second exception object of the second exception object type, the second exception object containing a second of the processing results, the generating of the second exception object resulting in a return to the immediately preceding calling method; and among the one or more calling methods, (i) calling the called method, (ii) in either the immediately preceding calling method or a higher level calling method: (iia) determining whether an object of the first exception object type has been generated by the called method, and if so then processing the normal processing result from the first exception object, and (iib) determining whether an object of the second exception object type has been generated by the called method, and if so then processing the second processing result from the second exception object; wherein the immediately preceding calling method is operative to: (i) determine whether an object of the first exception object type has been generated by the called method, and if so then process the normal processing result from the first exception object, and (ii) determine whether an object of the second exception object type has been generated by the called method, and if so then process the second processing result from the second exception object. 12. The computer system according to claim 7 , wherein the first and second exception object types are explicitly declared as being generated by the called methods so as to enable a compiler to check whether each is detected and processed within the calling methods.
| 0.541617 |
1. A method of identifying at least one speaker from a speech segment obtained by a computer by determining one or more words of the speech segment by identifying one or more portions of a sound wave having a sound wave contour between silences, the method comprising the steps of: the computer analyzing the sound wave contour of at least a portion of the sound wave to determine one or more variations within the sound wave contour; the computer assigning one or more features to the one or more variations by selecting a feature from a plurality of features based on slope characteristics of the sound wave contour representing the one or more portions of the sound wave having the sound wave contour between silences; the computer mapping one or more assigned features to one or more sound constructs, wherein the one or more sound constructs are at least part of a word; the computer determining parameters of the assigned features and order in which the parameters occur within the sound wave contour to indicate the start of a vowel in the speech segment; the computer grouping the parameters into predefined characteristics; the computer combining the predefined characteristics into a voice characteristic group; and the computer comparing the voice characteristic group to a plurality of existing voice characteristic groups each of the plurality of voice characteristic groups being attributed to one of the plurality of single speakers and, if the predefined characteristics of the voice characteristic group match the predefined characteristics of one of the plurality of existing voice characteristic groups, the computer assigning the sound construct to a speaker identified by the existing voice characteristic group matching the voice characteristic group.
|
1. A method of identifying at least one speaker from a speech segment obtained by a computer by determining one or more words of the speech segment by identifying one or more portions of a sound wave having a sound wave contour between silences, the method comprising the steps of: the computer analyzing the sound wave contour of at least a portion of the sound wave to determine one or more variations within the sound wave contour; the computer assigning one or more features to the one or more variations by selecting a feature from a plurality of features based on slope characteristics of the sound wave contour representing the one or more portions of the sound wave having the sound wave contour between silences; the computer mapping one or more assigned features to one or more sound constructs, wherein the one or more sound constructs are at least part of a word; the computer determining parameters of the assigned features and order in which the parameters occur within the sound wave contour to indicate the start of a vowel in the speech segment; the computer grouping the parameters into predefined characteristics; the computer combining the predefined characteristics into a voice characteristic group; and the computer comparing the voice characteristic group to a plurality of existing voice characteristic groups each of the plurality of voice characteristic groups being attributed to one of the plurality of single speakers and, if the predefined characteristics of the voice characteristic group match the predefined characteristics of one of the plurality of existing voice characteristic groups, the computer assigning the sound construct to a speaker identified by the existing voice characteristic group matching the voice characteristic group. 3. The method of claim 1 , wherein the plurality of features comprises: feature 1 having a characteristic of the sound wave varying rapidly around the zero value in positive and negative half-waves; feature 2 having a characteristic of a slope_change count of the sound wave being greater than a slope_zero count in a half-wave; feature 3 having a characteristic of slope_zero count being greater than zero and slope_change count being equal to zero in a half-wave; feature 4 having a characteristic of slope_change count being greater than zero and slope_zero count being equal to zero in a half-wave; feature 5 having a characteristic of slope_zero count being greater than slope_change count in a half-wave; feature 6 having a characteristic of slope_positive count being greater than zero in a half-wave; feature 7 having a characteristic of a slope_change count of the sound wave being greater than a slope_zero count in a half-wave, wherein the slope_change count occurs prior to the slope_zero count in the half-wave; and feature 8 having a characteristic of slope_zero count being greater than slope_change count in a half-wave, wherein the slope_zero count occurs prior to the slope_change count in the half-wave.
| 0.564252 |
1. A method of storing data associated with an electronic form, wherein the electronic form interacts with a business object, the method comprising: retrieving a first data field from a first data source, the first data source having a first protocol; retrieving a second data field from a second data source, the second data source having a second protocol, the second protocol being different than the first protocol; providing a graphical user interface where the first data field and the second data field are to be combined in the electronic form; allowing a third data field to be added to the form through the graphical user interface, wherein adding the third data field automatically changes a definition of the business object; and storing data indicative of the third field in a third data source, the third data source having a third protocol, the third protocol being different than the first protocol, the third protocol being different than the second protocol, wherein the first, second, and third data fields are part of a single business object.
|
1. A method of storing data associated with an electronic form, wherein the electronic form interacts with a business object, the method comprising: retrieving a first data field from a first data source, the first data source having a first protocol; retrieving a second data field from a second data source, the second data source having a second protocol, the second protocol being different than the first protocol; providing a graphical user interface where the first data field and the second data field are to be combined in the electronic form; allowing a third data field to be added to the form through the graphical user interface, wherein adding the third data field automatically changes a definition of the business object; and storing data indicative of the third field in a third data source, the third data source having a third protocol, the third protocol being different than the first protocol, the third protocol being different than the second protocol, wherein the first, second, and third data fields are part of a single business object. 11. The method of claim 1 , including displaying a setup sequence associated with the electronic form by: displaying a plurality of thumbnail images in a first area of a display, each of the thumbnail images representing a step in the setup sequence; displaying a full image in a second area of the display, the full image representing one of the steps in the setup sequence; detecting a first event associated with a thumbnail image in the plurality of thumbnail images; and displaying a popup image in response to detecting the first event, the popup image being a larger version of the thumbnail image associated with the first event.
| 0.614954 |
1. A method for data input, comprising the steps of: dividing an input selection device into multiple non-overlapping zones, wherein each non-overlapping zone includes two or more individual alphabetic or alphanumeric input selection indicators, wherein one of the alphabetic or alphanumeric input selection indicators in each non-overlapping zone is a jumper selector, and wherein the number of non-overlapping zones is less than the number of individual alphabetic or alphanumeric input selection indicators of the input selection device; receiving a user indication of two or more jumper selectors, wherein each jumper selector corresponds to a selected non-overlapping zone; collecting, into two or more characters sets, all of the individual alphabetic or alphanumeric input selection indicators associated with each selected non-overlapping zone; entering a sequence of the character sets into a parsing algorithm; and identifying, by the parsing algorithm and without further user input, one or more suggested words from a dictionary, wherein the identifying is based on the sequence of character sets.
|
1. A method for data input, comprising the steps of: dividing an input selection device into multiple non-overlapping zones, wherein each non-overlapping zone includes two or more individual alphabetic or alphanumeric input selection indicators, wherein one of the alphabetic or alphanumeric input selection indicators in each non-overlapping zone is a jumper selector, and wherein the number of non-overlapping zones is less than the number of individual alphabetic or alphanumeric input selection indicators of the input selection device; receiving a user indication of two or more jumper selectors, wherein each jumper selector corresponds to a selected non-overlapping zone; collecting, into two or more characters sets, all of the individual alphabetic or alphanumeric input selection indicators associated with each selected non-overlapping zone; entering a sequence of the character sets into a parsing algorithm; and identifying, by the parsing algorithm and without further user input, one or more suggested words from a dictionary, wherein the identifying is based on the sequence of character sets. 4. The method of claim 1 , wherein the input selection device is a keyboard with push-button characters.
| 0.654557 |
1. An accelerator for calculating distances for a speech recognition circuit, the accelerator comprising: a calculating circuit for calculating distances indicating the similarity between a feature vector and a plurality of predetermined acoustic states of an acoustic model, wherein the feature vector comprises a plurality of extracted and/or derived quantities from an audio signal during a defined audio time frame; first and second storage circuits, each for storing calculated distances for at least one said audio time frame, and for making said stored distances available for use by another part of the speech recognition circuit; and a control circuit for controlling read and write access to the first and second storage circuits, said control circuit being configured to allow writing to one said storage circuit while the other said storage circuit is available for reading, to allow first calculated distances for one audio time frame to be written to one said storage circuit while second calculated distances for an earlier audio time frame are made available for reading from the other said storage circuit.
|
1. An accelerator for calculating distances for a speech recognition circuit, the accelerator comprising: a calculating circuit for calculating distances indicating the similarity between a feature vector and a plurality of predetermined acoustic states of an acoustic model, wherein the feature vector comprises a plurality of extracted and/or derived quantities from an audio signal during a defined audio time frame; first and second storage circuits, each for storing calculated distances for at least one said audio time frame, and for making said stored distances available for use by another part of the speech recognition circuit; and a control circuit for controlling read and write access to the first and second storage circuits, said control circuit being configured to allow writing to one said storage circuit while the other said storage circuit is available for reading, to allow first calculated distances for one audio time frame to be written to one said storage circuit while second calculated distances for an earlier audio time frame are made available for reading from the other said storage circuit. 6. The accelerator of claim 1 , wherein the control circuit is adapted to release a result memory after a search stage has processed the contents, by informing the accelerator that it can overwrite the results in said memory.
| 0.532351 |
5. A method according to claim 1 further comprising: selecting, for all groups of corresponding data models, a group of corresponding class dependent data models or the corresponding independent data model based on a fit comparison and adding a selected data model or models to the final data model.
|
5. A method according to claim 1 further comprising: selecting, for all groups of corresponding data models, a group of corresponding class dependent data models or the corresponding independent data model based on a fit comparison and adding a selected data model or models to the final data model. 7. A method according to claim 5 wherein the cross entropy of the corresponding class dependent data models and the training data is calculated by calculating a logarithm likelihood of combined corresponding class dependent data models with regards to the training data.
| 0.956571 |
1. A computerized teaching system providing a teaching tool for presenting and teaching step by step solutions to STEM (science, technology, engineering and mathematics) questions, the system comprising: a communications network; at least one teacher computer operable by a respective teacher; at least one student computer operable by a respective student; and at least one computer-readable storage medium; wherein each of the at least one teacher computer and the at least one student computer includes an input device and a touch sensitive screen for receiving handwritten input via the input device; wherein the at least one student computer is operably connected to the at least one teacher computer via the communications network; and wherein the at least one teacher computer and the at least one student computer are operatively linked to the at least one computer-readable storage medium containing program instructions for implementing an application of the teaching system comprising one or more program instructions for performing the steps of: (a) receiving at least one question description being handwritten in algebraic math notation by the teacher on the touch sensitive screen of the at least one teacher computer and being displayed thereon; (b) highlighting the math notation of the at least one question description defined in step (a) using a first highlighting color to provide a highlighted math notation of the at least one question description; (c) displaying the highlighted math notation of the at least one question description of step (b) on the screen of the at least one student computer; (d) receiving at least one step of a step by step solution to the at least one question description, the at least one step being handwritten by the teacher in algebraic math notation on the screen of the at least one teacher computer and being displayed thereon; (e) highlighting the math notation of the at least one step in step (d) by either using the first highlighting color in step (b) if the math notation of the at least one step of step (d) is the algebraic equivalent of the math notation of the at least one question description of step (b) or using a second highlighting color if the math notation of the at least one step of step (d) is not the algebraic equivalent of the math notation of the at least one question description of step (b) to provide a highlighted math notation of the at least one step, the first highlighting color being different from the second highlighting color; (f) displaying the highlighted math notation of the at least one step of step (e) in one of the first highlighting color and the second highlighting color on the screen of the at least one student computer; and (g) repeating steps (d), (e) and (f), if necessary, to provide and display on the screen of the at least one student computer a completely color coded step by step solution to the at least one question description.
|
1. A computerized teaching system providing a teaching tool for presenting and teaching step by step solutions to STEM (science, technology, engineering and mathematics) questions, the system comprising: a communications network; at least one teacher computer operable by a respective teacher; at least one student computer operable by a respective student; and at least one computer-readable storage medium; wherein each of the at least one teacher computer and the at least one student computer includes an input device and a touch sensitive screen for receiving handwritten input via the input device; wherein the at least one student computer is operably connected to the at least one teacher computer via the communications network; and wherein the at least one teacher computer and the at least one student computer are operatively linked to the at least one computer-readable storage medium containing program instructions for implementing an application of the teaching system comprising one or more program instructions for performing the steps of: (a) receiving at least one question description being handwritten in algebraic math notation by the teacher on the touch sensitive screen of the at least one teacher computer and being displayed thereon; (b) highlighting the math notation of the at least one question description defined in step (a) using a first highlighting color to provide a highlighted math notation of the at least one question description; (c) displaying the highlighted math notation of the at least one question description of step (b) on the screen of the at least one student computer; (d) receiving at least one step of a step by step solution to the at least one question description, the at least one step being handwritten by the teacher in algebraic math notation on the screen of the at least one teacher computer and being displayed thereon; (e) highlighting the math notation of the at least one step in step (d) by either using the first highlighting color in step (b) if the math notation of the at least one step of step (d) is the algebraic equivalent of the math notation of the at least one question description of step (b) or using a second highlighting color if the math notation of the at least one step of step (d) is not the algebraic equivalent of the math notation of the at least one question description of step (b) to provide a highlighted math notation of the at least one step, the first highlighting color being different from the second highlighting color; (f) displaying the highlighted math notation of the at least one step of step (e) in one of the first highlighting color and the second highlighting color on the screen of the at least one student computer; and (g) repeating steps (d), (e) and (f), if necessary, to provide and display on the screen of the at least one student computer a completely color coded step by step solution to the at least one question description. 9. The system according to claim 1 , wherein the input device is a stylus.
| 0.573778 |
1. An autonomous biologically based learning system, comprising: a manufacturing tool that produces an asset; a drift component that modifies a manufacturing recipe processed by the manufacturing tool at least in part using a set of driving variables and a predetermined probability distribution function to generate one or more adjusted manufacturing recipes for the asset, wherein the set of driving variables determine a particular sequence to modify a set of recipe parameters associated with the manufacturing recipe; an objective autonomous learning engine that infers one or more functions for the manufacturing tool based on the modified manufacturing recipe processed by the manufacturing tool, wherein the one or more functions predict asset output metrics for the produced asset; and an autonomous optimization engine that extracts a set of updated recipe parameters from a set of input measurements and the one or more inferred functions to generate an adjusted recipe within a predefined tolerance of a target value for the asset output metrics.
|
1. An autonomous biologically based learning system, comprising: a manufacturing tool that produces an asset; a drift component that modifies a manufacturing recipe processed by the manufacturing tool at least in part using a set of driving variables and a predetermined probability distribution function to generate one or more adjusted manufacturing recipes for the asset, wherein the set of driving variables determine a particular sequence to modify a set of recipe parameters associated with the manufacturing recipe; an objective autonomous learning engine that infers one or more functions for the manufacturing tool based on the modified manufacturing recipe processed by the manufacturing tool, wherein the one or more functions predict asset output metrics for the produced asset; and an autonomous optimization engine that extracts a set of updated recipe parameters from a set of input measurements and the one or more inferred functions to generate an adjusted recipe within a predefined tolerance of a target value for the asset output metrics. 9. The system of claim 1 , wherein the autonomous optimization engine configures repair procedures in response to a determination that the adjusted recipe is not generated within the predefined tolerance of the target value for the asset output metrics.
| 0.613451 |
1. A method for providing information, the method comprising: receiving, at one or more processors, a natural language query; determining, at one or more processors, an answer to the natural language query; formatting, at one or more processors, one or more electronic messages that include: the answer, and metadata corresponding to the answer, the metadata separate from the answer and including information to enable construction by a computing device, using the metadata, of a syntactically correct natural language sentence or statement that recites and/or describes the answer, wherein the information to enable construction comprises information (i) indicating how the query was interpreted in determining the answer and (ii) not included in the query; and transmitting the one or more electronic messages via a communication network.
|
1. A method for providing information, the method comprising: receiving, at one or more processors, a natural language query; determining, at one or more processors, an answer to the natural language query; formatting, at one or more processors, one or more electronic messages that include: the answer, and metadata corresponding to the answer, the metadata separate from the answer and including information to enable construction by a computing device, using the metadata, of a syntactically correct natural language sentence or statement that recites and/or describes the answer, wherein the information to enable construction comprises information (i) indicating how the query was interpreted in determining the answer and (ii) not included in the query; and transmitting the one or more electronic messages via a communication network. 3. The method of claim 1 , wherein: the answer comprises an electronic object; and the metadata includes information to enable construction by the computing device, using the metadata, of the sentence or statement so that the sentence or statement describes the electronic object and/or contents of the electronic object.
| 0.617195 |
15. At a gesture recognition tutorial system including a motion-sensitive display surface capable of recognizing various forms of user interaction with the surface simultaneously from a plurality users, a method of providing a gesture tutorial mechanism for instructing one or more users how to properly enter program commands via the motion-sensitive display surface using gestures, the method comprising: determining that a received user-performed gesture is an unrecognized command, the gesture not corresponding to gesture commands recognized by one or more programs running on the gesture recognition tutorial system's motion-sensitive display surface; identifying one or more gesture commands similar to the received user-performed gesture that are recognized by a program of a motion-sensitive display surface, the motion-sensitive display surface being configured to detect multiple simultaneous user movements of objects over the surface from a plurality of simultaneous motion-sensitive display surface users, the surface being configured to recognize such multi-user interaction therewith; and based on the identified one or more gesture commands, displaying a visual example of a gesture capable of being performed on the motion-sensitive display surface, wherein the visual example of the gesture comprises one or more graphical, non-textual images that depict one or more motions a user can perform for executing the one or more gesture commands of a program running on the motion-sensitive display surface.
|
15. At a gesture recognition tutorial system including a motion-sensitive display surface capable of recognizing various forms of user interaction with the surface simultaneously from a plurality users, a method of providing a gesture tutorial mechanism for instructing one or more users how to properly enter program commands via the motion-sensitive display surface using gestures, the method comprising: determining that a received user-performed gesture is an unrecognized command, the gesture not corresponding to gesture commands recognized by one or more programs running on the gesture recognition tutorial system's motion-sensitive display surface; identifying one or more gesture commands similar to the received user-performed gesture that are recognized by a program of a motion-sensitive display surface, the motion-sensitive display surface being configured to detect multiple simultaneous user movements of objects over the surface from a plurality of simultaneous motion-sensitive display surface users, the surface being configured to recognize such multi-user interaction therewith; and based on the identified one or more gesture commands, displaying a visual example of a gesture capable of being performed on the motion-sensitive display surface, wherein the visual example of the gesture comprises one or more graphical, non-textual images that depict one or more motions a user can perform for executing the one or more gesture commands of a program running on the motion-sensitive display surface. 17. The method of claim 15 , wherein the visual example gesture corresponds to a command generally recognized by the gesture recognition tutorial system.
| 0.563492 |
14. A computing system for obtaining information for a user of a media playing device in a local home network, comprising: at least one processor; and at least one memory that stores computer readable instructions, which when executed by the computing system cause the computing system to: receive input from a user indicating that the user is interested in a search for further information about media playing on a consumer electronic device, the consumer electronic device being a television or a music player, the media being a movie or music, the consumer electronic device being coupled with one or more other user devices in a local home network; in response to receiving said input from the user, perform a plurality of search operations including a first search operation, a second search operation and a third search operation, the plurality of search operations being performed sequentially without requiring any other input from the user; and display information to the user based on results received in response to the third search operation; wherein the first search operation comprises: a first search for information on the one or more other user devices in the local home network based on characteristics of the media, wherein the first search includes obtaining information from metadata stored on at least one of the one or more other user devices in the local home network; and receiving contextual information from the local home network in response to the first search, wherein the contextual information received from the local home network is based at least in part on the metadata; wherein the second search operation comprises: a second search of the Internet based on the contextual information received from the local home network in response to the first search; and receiving results in response to the second search; wherein the third search operation comprises: a third search based on correlation data, wherein the correlation data indicates correlations between the contextual information received in response to the first search and the results received in response to the second search, and wherein the third search involves a search of the local home network and a search of an external network that is external to the local home network; and wherein the display of information to the user based on the results received in response to the third search operation comprises: determining, without user intervention, a relevant portion of the results received in response to the third search operation; and displaying information to the user that is based on the relevant portion and not based on other portions of the results received in response to the third search operation.
|
14. A computing system for obtaining information for a user of a media playing device in a local home network, comprising: at least one processor; and at least one memory that stores computer readable instructions, which when executed by the computing system cause the computing system to: receive input from a user indicating that the user is interested in a search for further information about media playing on a consumer electronic device, the consumer electronic device being a television or a music player, the media being a movie or music, the consumer electronic device being coupled with one or more other user devices in a local home network; in response to receiving said input from the user, perform a plurality of search operations including a first search operation, a second search operation and a third search operation, the plurality of search operations being performed sequentially without requiring any other input from the user; and display information to the user based on results received in response to the third search operation; wherein the first search operation comprises: a first search for information on the one or more other user devices in the local home network based on characteristics of the media, wherein the first search includes obtaining information from metadata stored on at least one of the one or more other user devices in the local home network; and receiving contextual information from the local home network in response to the first search, wherein the contextual information received from the local home network is based at least in part on the metadata; wherein the second search operation comprises: a second search of the Internet based on the contextual information received from the local home network in response to the first search; and receiving results in response to the second search; wherein the third search operation comprises: a third search based on correlation data, wherein the correlation data indicates correlations between the contextual information received in response to the first search and the results received in response to the second search, and wherein the third search involves a search of the local home network and a search of an external network that is external to the local home network; and wherein the display of information to the user based on the results received in response to the third search operation comprises: determining, without user intervention, a relevant portion of the results received in response to the third search operation; and displaying information to the user that is based on the relevant portion and not based on other portions of the results received in response to the third search operation. 23. A computing system as recited in claim 14 wherein the computer readable instructions, when executed by the computing system, further cause the computing system to: send, during the second search, a query to a search engine on the Internet, the query being based on the contextual information received from the local home network in response to the first search; receive, in response to the query, a plurality of Uniform Resource Locators (URLs) from the search engine and a corresponding plurality of web page snippets, each web snippet being a portion of all text found at a web page for the corresponding URL; analyze the web page snippets to determine relevant portions of the snippets; and extract relevant portions from the snippets wherein the third search operation is based on the extracted relevant portions.
| 0.529225 |
3. The method of claim 2 wherein the semantic model comprises: a tensor function that generates a tensor based on two syntactic vectors; a first matrix function that generates a first matrix based on two syntactic vectors; a second matrix function that generates a second matrix based on two syntactic vectors; and an offset function that generates an offset vector based on two syntactic vectors.
|
3. The method of claim 2 wherein the semantic model comprises: a tensor function that generates a tensor based on two syntactic vectors; a first matrix function that generates a first matrix based on two syntactic vectors; a second matrix function that generates a second matrix based on two syntactic vectors; and an offset function that generates an offset vector based on two syntactic vectors. 4. The method of claim 3 wherein generating the semantic representation corresponding to the selected non-leaf node of the dependency structure comprises: obtaining a first syntactic vector corresponding to a first parent node of the selected non-leaf node; obtaining a second syntactic vector corresponding to a second parent node of the selected non-leaf node; generating the tensor by applying the tensor function to the first syntactic vector and the second syntactic vector; generating the first matrix by applying the first matrix function to the first syntactic vector and the second syntactic vector; generating the second matrix by applying the second matrix function to the first syntactic vector and the second syntactic vector; and generating the offset vector by applying the offset function to the first syntactic vector and the second syntactic vector.
| 0.758176 |
1. A computer-assisted language generation system comprising: sentence retrieval functionality, operative on the basis of an input text containing words, to retrieve from an internet corpus a plurality of sentences containing words which correspond to said words in the input text; and sentence generation functionality operative using said plurality of sentences to generate at least one correct sentence giving expression to the input text, said sentence generation functionality comprising: sentence simplification functionality operative to simplify said sentences retrieved from said internet corpus by: classifying all words of each of said sentences retrieved from said internet corpus as being one of unnecessary and mandatory, said unnecessary words comprising words which are at least one of adjectives, adverbs, articles, prepositions, predefined list of unnecessary words, said mandatory words comprising words which are not unnecessary words; deleting unnecessary words from each of said sentences: ascertaining, for each phrase of each of said sentences, whether said phrase comprises at least one of at least one word in said input text and at least one alternative word of at least one word in said input text; and responsive to ascertaining that said phrase does not comprise at least one of at least one word in said input text and at least one alternative word of at least one word in said input text, deleting said phrase from said sentence: simplified sentence grouping functionality for grouping similar simplified sentences provided by said sentence simplification functionality; simplified sentence group ranking functionality for ranking groups of said similar simplified sentences; and sentence selection functionality operative to select at least one of said similar simplified sentences as said at least one correct sentence based on said ranking.
|
1. A computer-assisted language generation system comprising: sentence retrieval functionality, operative on the basis of an input text containing words, to retrieve from an internet corpus a plurality of sentences containing words which correspond to said words in the input text; and sentence generation functionality operative using said plurality of sentences to generate at least one correct sentence giving expression to the input text, said sentence generation functionality comprising: sentence simplification functionality operative to simplify said sentences retrieved from said internet corpus by: classifying all words of each of said sentences retrieved from said internet corpus as being one of unnecessary and mandatory, said unnecessary words comprising words which are at least one of adjectives, adverbs, articles, prepositions, predefined list of unnecessary words, said mandatory words comprising words which are not unnecessary words; deleting unnecessary words from each of said sentences: ascertaining, for each phrase of each of said sentences, whether said phrase comprises at least one of at least one word in said input text and at least one alternative word of at least one word in said input text; and responsive to ascertaining that said phrase does not comprise at least one of at least one word in said input text and at least one alternative word of at least one word in said input text, deleting said phrase from said sentence: simplified sentence grouping functionality for grouping similar simplified sentences provided by said sentence simplification functionality; simplified sentence group ranking functionality for ranking groups of said similar simplified sentences; and sentence selection functionality operative to select at least one of said similar simplified sentences as said at least one correct sentence based on said ranking. 11. A system according to claim 1 and also comprising: a misused-word suspector evaluating, words in said input text; an alternatives generator, generating multiple alternatives for at least some of the words in said input text evaluated as suspect words by said suspector, at least one of said multiple alternatives for a word in said input text being consistent with a contextual feature of said word in said input text in an internet corpus; a selector for selecting among at least said multiple alternatives; and a correction generator operative to provide a correction output based at least partially on a selection made by said selector.
| 0.604965 |
5. A system of classifying marking types on images of a document, the system comprising: a segmenter operated on a processor and configured to receive the document containing the images, the segmenter segmenting the images into fragments of foreground pixel structures that are identified as being likely to be of the same marking type by finding connected components, and dividing at least some of the connected components to obtain image fragments, the connected components being isolated, continuous regions of foreground pixels, the segmenter segmenting the images by: identifying neatly written or printed text by grouping selected feature points along predetermined orientations, the feature points being local extrema of bounding contours of the connected components; and subtracting enclosing boundary boxes of text lines from remaining document material to fragment connected components that are partly part of the text lines and partly part of extraneous markings; and a classifier operated on a processor and configured to receive the fragments, the classifier providing a category score to each received fragment, wherein the classifier is trained from ground truth images whose pixels are labeled according to known marking types, the classifier assigning a same label to all pixels in a fragment when the fragment is classified by the classifier.
|
5. A system of classifying marking types on images of a document, the system comprising: a segmenter operated on a processor and configured to receive the document containing the images, the segmenter segmenting the images into fragments of foreground pixel structures that are identified as being likely to be of the same marking type by finding connected components, and dividing at least some of the connected components to obtain image fragments, the connected components being isolated, continuous regions of foreground pixels, the segmenter segmenting the images by: identifying neatly written or printed text by grouping selected feature points along predetermined orientations, the feature points being local extrema of bounding contours of the connected components; and subtracting enclosing boundary boxes of text lines from remaining document material to fragment connected components that are partly part of the text lines and partly part of extraneous markings; and a classifier operated on a processor and configured to receive the fragments, the classifier providing a category score to each received fragment, wherein the classifier is trained from ground truth images whose pixels are labeled according to known marking types, the classifier assigning a same label to all pixels in a fragment when the fragment is classified by the classifier. 15. The system according to claim 5 , wherein the segmenter segments the images by further: determining the enclosing boundary boxes for individual text lines based on the grouping.
| 0.786205 |
13. A computer program, residing on a computer-readable medium, comprising instructions for causing a computer to: convert a stream of digitized speech samples to a stream of text and associated reliability measures, the reliability measures indicating a level of confidence in the correctness of the speech to text conversion of the associated portions of the stream of text; and create a mixed-media data stream comprising the stream of text as a text component and selected portions of the digitized stream of speech as a speech component, each selected portion corresponding to a portion of the stream of text having a reliability measure below a threshold.
|
13. A computer program, residing on a computer-readable medium, comprising instructions for causing a computer to: convert a stream of digitized speech samples to a stream of text and associated reliability measures, the reliability measures indicating a level of confidence in the correctness of the speech to text conversion of the associated portions of the stream of text; and create a mixed-media data stream comprising the stream of text as a text component and selected portions of the digitized stream of speech as a speech component, each selected portion corresponding to a portion of the stream of text having a reliability measure below a threshold. 20. The method of claim 13, wherein the mixed-media data stream is created from two time-synchronized data streams, the first being the original data stream of digitized speech samples, and the second being the stream of text having associated reliability measures.
| 0.634234 |
27. A method of extracting data of interest from at least one of a plurality of web sites, wherein the data of interest is information associated with a product, the method comprising: (A) for each respective web site W in said plurality of web sites, (i) creating a respective description of data of interest that identifies the web site W; (ii) developing an extraction pattern from a web page output from the respective web site W using a graphical user interface tool, the extraction pattern being adapted to identify at least a portion of an output of a web site and to extract information from a plurality of web pages of the respective web site W, wherein the extraction pattern comprises a pre-condition regular expression, a portion of data of interest regular expression, and a post-condition regular expression, said developing an extraction pattern comprising refining at least one of said pre-condition regular expression, said portion of data of interest regular expression, and said post-condition regular expression; and (iii) associating the developed extraction pattern with the respective description of data of interest for the respective web site W; (B) receiving a value for use as an extraction parameter for the developed extraction patterns; and (C) obtaining the data of interest by querying the at least one web site of the plurality of web sites using the value and the extraction patterns associated with the respective descriptions of data of interest; and (D) extracting said data of interest from the at least one web site of the plurality of web sites and storing said extracted data of interest.
|
27. A method of extracting data of interest from at least one of a plurality of web sites, wherein the data of interest is information associated with a product, the method comprising: (A) for each respective web site W in said plurality of web sites, (i) creating a respective description of data of interest that identifies the web site W; (ii) developing an extraction pattern from a web page output from the respective web site W using a graphical user interface tool, the extraction pattern being adapted to identify at least a portion of an output of a web site and to extract information from a plurality of web pages of the respective web site W, wherein the extraction pattern comprises a pre-condition regular expression, a portion of data of interest regular expression, and a post-condition regular expression, said developing an extraction pattern comprising refining at least one of said pre-condition regular expression, said portion of data of interest regular expression, and said post-condition regular expression; and (iii) associating the developed extraction pattern with the respective description of data of interest for the respective web site W; (B) receiving a value for use as an extraction parameter for the developed extraction patterns; and (C) obtaining the data of interest by querying the at least one web site of the plurality of web sites using the value and the extraction patterns associated with the respective descriptions of data of interest; and (D) extracting said data of interest from the at least one web site of the plurality of web sites and storing said extracted data of interest. 29. The method of claim 27 , wherein when the data of interest includes data of interest from at least two web sites of the plurality of web sites, the data of interest from the at least two web sites is extracted.
| 0.5 |
1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: a) providing a set of content items, each content item having at least one associated descriptive term to describe the content item; b) receiving incremental input entered by the user for incrementally identifying desired content items; c) in response to the incremental input entered by the user, presenting a subset of content items; d) receiving selection actions of content items of the subset from the user; e) analyzing the descriptive terms associated with the selected content items to learn the preferred descriptive terms of the user; f) expressing the learned preferred descriptive terms as a segmented measurement collection having at least one fine grain segment and at least one coarse grain segment, wherein the fine grain segment has fine grain differentiation of measurements associated with preferred descriptive terms within the segment, and wherein the coarse grain segment has relatively coarse grain differentiation of measurements associated with preferred descriptive terms within the segment; and g) in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented measurement collection; h) wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device.
|
1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: a) providing a set of content items, each content item having at least one associated descriptive term to describe the content item; b) receiving incremental input entered by the user for incrementally identifying desired content items; c) in response to the incremental input entered by the user, presenting a subset of content items; d) receiving selection actions of content items of the subset from the user; e) analyzing the descriptive terms associated with the selected content items to learn the preferred descriptive terms of the user; f) expressing the learned preferred descriptive terms as a segmented measurement collection having at least one fine grain segment and at least one coarse grain segment, wherein the fine grain segment has fine grain differentiation of measurements associated with preferred descriptive terms within the segment, and wherein the coarse grain segment has relatively coarse grain differentiation of measurements associated with preferred descriptive terms within the segment; and g) in response to receiving subsequent incremental input entered by the user, selecting and ordering a collection of content items by promoting the ranking of content items associated with the learned preferred descriptive terms of the user according to the differentiation provided by the segmented measurement collection; h) wherein at least one of the incremental input and the subsequent incremental input are entered by the user on an input constrained device. 24. The method of claim 1 , wherein at least one of receiving incremental input, presenting the subset of content items, receiving selection actions, analyzing the descriptive terms, expressing the learned preferred descriptive terms as a segmented measurement collection, and selecting and ordering the collection of content items is performed on a user client device.
| 0.620613 |
4. The method of claim 1 , wherein correlating includes computing a correlation score for each change serving as a candidate cause for the incident that indicates a relative likelihood of the occurrence of that change as a cause of the incident.
|
4. The method of claim 1 , wherein correlating includes computing a correlation score for each change serving as a candidate cause for the incident that indicates a relative likelihood of the occurrence of that change as a cause of the incident. 5. The method of claim 4 , further comprising identifying the one or more candidate causes with a highest correlation score as a cause for the incident.
| 0.95468 |
14. A computer executable program stored on a computer-readable storage medium and configured to make a computer manage electronically recorded document files, the program comprising instructions for performing the steps of: a step for inputting information by an operator; a step for editing a virtual combination object based on the information inputted in said input step, the virtual combination object denoting an object that has a first data region and virtually combining document files, wherein the first data region includes information for managing the document files to be virtually combined, including an order relation between the document files, and a setting position of the index object to be set immediately before or immediately after the virtually combined document file, or immediately before or immediately after a page constituting the document file; a step for editing an index object based on the information inputted in said input step, the index object denoting an object that has a second data region and manages at least one or more document files included in the document files virtually combined by the virtual combination object or one or more pages constituting the document file, a s a subgroup in the virtual combination object, wherein the second data region includes information on setting for processing the subgroup and a parameter according to the process setting; and a step for managing and processing the document files based on the information recorded in the virtual combination object and the index object.
|
14. A computer executable program stored on a computer-readable storage medium and configured to make a computer manage electronically recorded document files, the program comprising instructions for performing the steps of: a step for inputting information by an operator; a step for editing a virtual combination object based on the information inputted in said input step, the virtual combination object denoting an object that has a first data region and virtually combining document files, wherein the first data region includes information for managing the document files to be virtually combined, including an order relation between the document files, and a setting position of the index object to be set immediately before or immediately after the virtually combined document file, or immediately before or immediately after a page constituting the document file; a step for editing an index object based on the information inputted in said input step, the index object denoting an object that has a second data region and manages at least one or more document files included in the document files virtually combined by the virtual combination object or one or more pages constituting the document file, a s a subgroup in the virtual combination object, wherein the second data region includes information on setting for processing the subgroup and a parameter according to the process setting; and a step for managing and processing the document files based on the information recorded in the virtual combination object and the index object. 22. The computer executable program according to claim 14 , wherein said virtual combination editing step decomposes the virtual combination of the virtual combination object to create the document file or document files not virtually combined by the virtual combination object or a new virtual combination object or new virtual combination objects in which at least part of the document files are virtually combined.
| 0.66867 |
17. A system for hosting a website editor application, the system comprising a processor and a computer readable storage medium comprising program code executable by the processor, the program code comprising: an editor display component configured to display an editor interface for receiving user input for editing a website, the editor interface configured for display within a browser simultaneously with the website, the editor display component comprising: a menu design interface, the menu design interface for allowing a user to modify media content of the website and comprising a simulated website menu representing a website menu; wherein the menu design interface allows a user to drag and drop media content from a media library to a simulated website menu to create an associated webpage; a website modification component configured to update website data corresponding to the website based on the user input received through the editor interface, the website data defining the display and content of the website; a website display component configured to automatically update display of the website based on the updated website data, wherein the website display component updates display of the website in real-time in response to receiving the user input; and a web hosting component configured to provide the editor display component to a browser of a client device over a network.
|
17. A system for hosting a website editor application, the system comprising a processor and a computer readable storage medium comprising program code executable by the processor, the program code comprising: an editor display component configured to display an editor interface for receiving user input for editing a website, the editor interface configured for display within a browser simultaneously with the website, the editor display component comprising: a menu design interface, the menu design interface for allowing a user to modify media content of the website and comprising a simulated website menu representing a website menu; wherein the menu design interface allows a user to drag and drop media content from a media library to a simulated website menu to create an associated webpage; a website modification component configured to update website data corresponding to the website based on the user input received through the editor interface, the website data defining the display and content of the website; a website display component configured to automatically update display of the website based on the updated website data, wherein the website display component updates display of the website in real-time in response to receiving the user input; and a web hosting component configured to provide the editor display component to a browser of a client device over a network. 18. The system of claim 17 , wherein the editor display component comprises code executable within a browser of a client device.
| 0.504892 |
1. A method for compressing a grammar, the method comprising: receiving a grammar to be compressed by using a computer, the grammar comprising a set of rules, each rule comprising a set of token classes, wherein a token class is a logical grouping of tokens, and a token is a string of one or more characters; parsing the grammar to identify the set of rules within the grammar and the set of token classes within each rule; eliminating, from the grammar, all but one of any duplicate rules identified from parsing the grammar, wherein duplicate rules include rules having the same token classes in the same order; identifying, from the set of token classes within each remaining rule, a set of unimportant token classes separate from a set of important token classes, where the set of unimportant token classes are eligible for compression; analyzing the set of unimportant token classes to identify two or more token classes within the set of unimportant token classes that are similar; merging the two or more token classes within the set of unimportant token classes identified from the currently received grammar to generate a merged token class by removing duplicate tokens and combining remaining tokens from the two or more token classes; and substituting the merged token class in the grammar for the two or more token classes that were merged to generate the merged token class to generate a compressed grammar.
|
1. A method for compressing a grammar, the method comprising: receiving a grammar to be compressed by using a computer, the grammar comprising a set of rules, each rule comprising a set of token classes, wherein a token class is a logical grouping of tokens, and a token is a string of one or more characters; parsing the grammar to identify the set of rules within the grammar and the set of token classes within each rule; eliminating, from the grammar, all but one of any duplicate rules identified from parsing the grammar, wherein duplicate rules include rules having the same token classes in the same order; identifying, from the set of token classes within each remaining rule, a set of unimportant token classes separate from a set of important token classes, where the set of unimportant token classes are eligible for compression; analyzing the set of unimportant token classes to identify two or more token classes within the set of unimportant token classes that are similar; merging the two or more token classes within the set of unimportant token classes identified from the currently received grammar to generate a merged token class by removing duplicate tokens and combining remaining tokens from the two or more token classes; and substituting the merged token class in the grammar for the two or more token classes that were merged to generate the merged token class to generate a compressed grammar. 8. The method of claim 1 , wherein merging the two or more unimportant token classes from the candidate subset to generate a merged token class comprises generating a duplicate-free union of tokens included in each of the two or more unimportant token classes from the candidate subset.
| 0.761946 |
1. A method for use in connection with generating text, the method comprising: using at least one computer hardware processor to perform: obtaining a plurality of items of content and associated metadata, the associated metadata comprising information indicative of how persuasive at least one of the plurality of items of content is likely to be to a person; obtaining a schema specifying a first set of one or more rhetorical relations; identifying a second set of one or more rhetorical relations among items of content in the plurality of items of content based, at least in part, on the associated metadata, wherein the second set of rhetorical relations is not in the schema; generating a document plan comprising a plurality of rhetorical relations among the items of content in the plurality of items of content, the plurality of rhetorical relations including the first set of rhetorical relations and the second set of rhetorical relations; generating an electronic document comprising natural language text based, at least in part, on the document plan; and providing the electronic document to the person.
|
1. A method for use in connection with generating text, the method comprising: using at least one computer hardware processor to perform: obtaining a plurality of items of content and associated metadata, the associated metadata comprising information indicative of how persuasive at least one of the plurality of items of content is likely to be to a person; obtaining a schema specifying a first set of one or more rhetorical relations; identifying a second set of one or more rhetorical relations among items of content in the plurality of items of content based, at least in part, on the associated metadata, wherein the second set of rhetorical relations is not in the schema; generating a document plan comprising a plurality of rhetorical relations among the items of content in the plurality of items of content, the plurality of rhetorical relations including the first set of rhetorical relations and the second set of rhetorical relations; generating an electronic document comprising natural language text based, at least in part, on the document plan; and providing the electronic document to the person. 9. The method of claim 1 , wherein the plurality of items of content comprises a first item of content and a second item of content, and wherein identifying the second set of rhetorical relations comprises determining whether the first item of content and the second item of content satisfy at least one rhetorical relation based, at least in part, on metadata associated with the first item of content and metadata associated with the second item of content.
| 0.620317 |
15. A program product comprising a non-transitory computer readable storage medium that stores code executable by a processor, the executable code comprising code to perform: recognizing two or more logogram radicals; and generating one or more logogram phrases for the two or more logogram radicals, wherein each logogram phrase comprises a first logogram embodying a first logogram radical of the two or more logogram radicals and a second logogram embodying a second logogram radical of the two or more logogram radicals.
|
15. A program product comprising a non-transitory computer readable storage medium that stores code executable by a processor, the executable code comprising code to perform: recognizing two or more logogram radicals; and generating one or more logogram phrases for the two or more logogram radicals, wherein each logogram phrase comprises a first logogram embodying a first logogram radical of the two or more logogram radicals and a second logogram embodying a second logogram radical of the two or more logogram radicals. 18. The program product of claim 15 , the code further performing: displaying a first logogram list of logograms embodying the first logogram radical of the two or more logogram radicals based on a usage history; and receiving a selection of a first logogram from the first logogram list, wherein the one or more logogram phrases are generated in response to the first logogram and the second logogram radical of the two or more logogram radicals.
| 0.529057 |
8. The method of claim 1 , further comprising: engaging in a dialog with the user, including: receiving input from the user, producing a voice markup language script in response to the user input, and executing the voice markup language script to generate an output for provision to the user.
|
8. The method of claim 1 , further comprising: engaging in a dialog with the user, including: receiving input from the user, producing a voice markup language script in response to the user input, and executing the voice markup language script to generate an output for provision to the user. 10. The method of claim 8 , wherein engaging in a dialog with the user further comprises: receiving a second user input when an output based on the executed voice markup language script is being provided to the user; interrupting the output being provided to the user; and processing the second user input.
| 0.792994 |
1. A method for context based routing of messages, comprising: receiving a message for routing by a message switch implemented in a hardware processor; parsing the message to identify a topic and a data payload of the message; identifying a topic queue to which to route the message based on the topic and the data payload; routing the message to the topic queue; executing automatically a template integration process subscribing to the topic queue, in response to the message being routed to the topic queue, the template integration process comprising a configurable and executable template that provides a service, the template integration process invoking an application service for providing the service, with a request comprising data extracted from the message for the application service to handle the request, the template integration process receiving a result of handling of the service from the application service.
|
1. A method for context based routing of messages, comprising: receiving a message for routing by a message switch implemented in a hardware processor; parsing the message to identify a topic and a data payload of the message; identifying a topic queue to which to route the message based on the topic and the data payload; routing the message to the topic queue; executing automatically a template integration process subscribing to the topic queue, in response to the message being routed to the topic queue, the template integration process comprising a configurable and executable template that provides a service, the template integration process invoking an application service for providing the service, with a request comprising data extracted from the message for the application service to handle the request, the template integration process receiving a result of handling of the service from the application service. 7. The method of claim 1 , wherein the template integration process is preconfigured to invoke the application service in response to the message being routed to the topic queue.
| 0.588723 |
6. The computer implemented method of claim 1 , wherein generating the desirability factor comprises generating an uncertainty value for each instance in the case, the uncertainty value is based, at least in part, on the proximity of the classification score to a classification threshold, and the desirability factor is based, at least in part, on the uncertainty values.
|
6. The computer implemented method of claim 1 , wherein generating the desirability factor comprises generating an uncertainty value for each instance in the case, the uncertainty value is based, at least in part, on the proximity of the classification score to a classification threshold, and the desirability factor is based, at least in part, on the uncertainty values. 7. The computer implemented method of claim 6 , wherein generating the desirability factor comprises summing the uncertainty values.
| 0.857563 |
53. The system of claim 42 further comprising: means for displaying the first corresponding instructions of the source program in the ladder-based language, as edited, as a ladder diagram on a display device; and means for displaying the second corresponding instructions of the source program in the high-level text-based language as text on the display device.
|
53. The system of claim 42 further comprising: means for displaying the first corresponding instructions of the source program in the ladder-based language, as edited, as a ladder diagram on a display device; and means for displaying the second corresponding instructions of the source program in the high-level text-based language as text on the display device. 54. The system of claim 53 wherein the first display interfacing means and the second display interfacing means display the ladder diagram and the text simultaneously and wherein the ladder diagram corresponds to the same at least one of the one or more instructions of the source program as the text.
| 0.832618 |
32. A computer-implemented method of segmenting images according to claim 23 in which the learning model comprises a reinforcement learning model.
|
32. A computer-implemented method of segmenting images according to claim 23 in which the learning model comprises a reinforcement learning model. 33. A computer-implemented method of segmenting images according to claim 32 in which the reinforcement learning model comprises a Q-learning model which generates the at least one segmentation parameter from at least one image feature and provides a reward or a punishment to itself in response to an action comprising a change of the at least one segmentation parameter.
| 0.849145 |
1. A method, comprising: receiving, at a computer system in a computer network, information regarding multiple data attributes associated with an application; analyzing, by the computer system, the data attributes to determine cardinality information of the data attributes; predicting, by the computer system and based at least in part on a set of queries received at the computer system, a set of the data attributes to be requested in the future; generating, by the computer system and based at least in part on the cardinality information and the set of the data attributes, multiple tables, wherein different tables have different subsets of the data attributes as columns of the tables, wherein the multiple tables include a first table and a second table, wherein the first table and the second table both contain at least some common columns; receiving, at the computer system and from an entity, a query having a plurality of query parameters; selecting, by the computer system, one of the multiple tables in a storage system to obtain query results from, wherein selecting the one of the multiple tables includes: analyzing the multiple tables to determine a prefix of each of the multiple tables, and selecting a specified table of the multiple tables that has a longest common prefix with the query parameters, the longest common prefix being one of the determined prefixes containing a longest sequence of a plurality of leading columns that matches with a portion of the query parameters; and obtaining, in response to the query, the query results from the specified table.
|
1. A method, comprising: receiving, at a computer system in a computer network, information regarding multiple data attributes associated with an application; analyzing, by the computer system, the data attributes to determine cardinality information of the data attributes; predicting, by the computer system and based at least in part on a set of queries received at the computer system, a set of the data attributes to be requested in the future; generating, by the computer system and based at least in part on the cardinality information and the set of the data attributes, multiple tables, wherein different tables have different subsets of the data attributes as columns of the tables, wherein the multiple tables include a first table and a second table, wherein the first table and the second table both contain at least some common columns; receiving, at the computer system and from an entity, a query having a plurality of query parameters; selecting, by the computer system, one of the multiple tables in a storage system to obtain query results from, wherein selecting the one of the multiple tables includes: analyzing the multiple tables to determine a prefix of each of the multiple tables, and selecting a specified table of the multiple tables that has a longest common prefix with the query parameters, the longest common prefix being one of the determined prefixes containing a longest sequence of a plurality of leading columns that matches with a portion of the query parameters; and obtaining, in response to the query, the query results from the specified table. 5. The method of claim 1 , wherein generating the tables includes: receiving the set of the data attributes as a user selection of a first list of columns, wherein the first list of columns is a subset of a finite set of columns on which potential user queries can be executed, determining the cardinality information of the first list of columns, expressing at least the first list of columns and the cardinality information of the first list of columns as a meta query language, determining different subsets of the finite set of columns using the meta query language, and generating the tables with the determined different subsets of the finite set of columns.
| 0.561195 |
1. A method comprising: receiving, by a computing device, a request from a user identifying a renderable media item; creating, by the computing device, a semantic icon from a tag in an annotation associated with a first time in the media item; and transmitting, by the computing device, a graphical user interface to the user for display, the graphical user interface showing the semantic icon on a timeline as a representation of the annotation, the semantic icon being displayed in a first size and, upon selection by the user, changes to a second size corresponding to a size of a segment of the media item.
|
1. A method comprising: receiving, by a computing device, a request from a user identifying a renderable media item; creating, by the computing device, a semantic icon from a tag in an annotation associated with a first time in the media item; and transmitting, by the computing device, a graphical user interface to the user for display, the graphical user interface showing the semantic icon on a timeline as a representation of the annotation, the semantic icon being displayed in a first size and, upon selection by the user, changes to a second size corresponding to a size of a segment of the media item. 9. The method of claim 1 , wherein the tag is selected from an image, a video item, and an audio item.
| 0.703424 |
11. The computer of claim 10 wherein the computer-executable instructions are for performing steps that further comprise: receiving a second indication that is indicative of a selected keyphrase, the selected keyphrase being one of the related keyphrases.
|
11. The computer of claim 10 wherein the computer-executable instructions are for performing steps that further comprise: receiving a second indication that is indicative of a selected keyphrase, the selected keyphrase being one of the related keyphrases. 12. The computer of claim 11 wherein the computer-executable instructions for performing steps that further comprise: highlighting the selected keyphrase on a display device.
| 0.942108 |
14. A method according to claim 1 , wherein the receiving, by a device, a request for a modification to the business document comprises: receiving, by the device operated by the first party, the request for the modification to the business document; and wherein the editing, by a device, the business document comprises: editing, by the device operated by the first party, the business document.
|
14. A method according to claim 1 , wherein the receiving, by a device, a request for a modification to the business document comprises: receiving, by the device operated by the first party, the request for the modification to the business document; and wherein the editing, by a device, the business document comprises: editing, by the device operated by the first party, the business document. 15. A method according to claim 14 , wherein the first party is an employee of an entity, the second party is a customer of the entity and the third party is a manager of the employee of the entity.
| 0.943443 |
65. A system to assist an information security classification process of an organization for security classification and marking of an electronic document, said system comprising at least one computer system, where said at least one computer system comprising at least one electronic storage medium, where said at least one electronic storage medium comprising at least one software engine, where said at least one software engine comprising: a. establish an electronic document security regimen comprising at least one criterion of an information security classification process, b. display a user classification dialogue for at least one informational portion of an electronic document, where said user classification dialogue comprising a menu of choices, where said menu of choices comprising at least one element for selection, and where said at least one element is associated with said at least one criterion of said electronic document security regimen, c. retrieve said at least one element, where said at least one element is selected, d. establish a classification mark from said at least one criterion associated with the retrieved said at least one element, and e. insert said classification mark into said electronic document.
|
65. A system to assist an information security classification process of an organization for security classification and marking of an electronic document, said system comprising at least one computer system, where said at least one computer system comprising at least one electronic storage medium, where said at least one electronic storage medium comprising at least one software engine, where said at least one software engine comprising: a. establish an electronic document security regimen comprising at least one criterion of an information security classification process, b. display a user classification dialogue for at least one informational portion of an electronic document, where said user classification dialogue comprising a menu of choices, where said menu of choices comprising at least one element for selection, and where said at least one element is associated with said at least one criterion of said electronic document security regimen, c. retrieve said at least one element, where said at least one element is selected, d. establish a classification mark from said at least one criterion associated with the retrieved said at least one element, and e. insert said classification mark into said electronic document. 81. The system of claim 65 , wherein said at least one criterion comprising at least one designator, where said at least one designator comprising at least one of: a. a national security classification, b. a sensitive classification, or c. an unclassified classification.
| 0.573329 |
11. A text-to-speech method for a mobile communication terminal that is capable of displaying multiple objects on a screen in an overlapping manner, the method comprising: identifying a characteristic of an activated object on the screen; finding a speech data mapped to the identified characteristic; and outputting an audible signal corresponding to textual contents of the activated object using the speech data.
|
11. A text-to-speech method for a mobile communication terminal that is capable of displaying multiple objects on a screen in an overlapping manner, the method comprising: identifying a characteristic of an activated object on the screen; finding a speech data mapped to the identified characteristic; and outputting an audible signal corresponding to textual contents of the activated object using the speech data. 13. The text-to-speech method of claim 11 , further comprising storing a plurality of speech data and information regarding mappings between characteristics of objects and the speech data.
| 0.74541 |
30. The apparatus of claim 18 , wherein each atlas image comprises a plurality of points, each atlas image point being associated with a label indicative of whether the associated atlas image point is classified as the at least one structure, wherein registering the subject image with a plurality of the atlas images associates the registered subject image points with the labels that are associated with the atlas image points that were mapped to the registered subject image points, and wherein the processor is further configured to generate the first data by combining the labels associated with the registered subject image points according to a lab& fusion technique.
|
30. The apparatus of claim 18 , wherein each atlas image comprises a plurality of points, each atlas image point being associated with a label indicative of whether the associated atlas image point is classified as the at least one structure, wherein registering the subject image with a plurality of the atlas images associates the registered subject image points with the labels that are associated with the atlas image points that were mapped to the registered subject image points, and wherein the processor is further configured to generate the first data by combining the labels associated with the registered subject image points according to a lab& fusion technique. 31. The apparatus of claim 30 , wherein the generated first data comprises a plurality of first data labels associated with a plurality of the subject image points, each first data label is indicative whether its associated subject image point belongs to the at least one structure, the generated second data comprises a plurality of second data labels associated with a plurality of the subject image points, and each second data label is indicative whether its associated subject image point belongs to the at least one structure, and wherein the processor is further configured to combine, for at least the subject image points for which their associated first data labels and second data labels are in disagreement as to whether the associated subject image points belong the at least one structure, the associated first data and second data labels according to a label fusion technique.
| 0.625134 |
1. A method comprising: by one or more computer systems, analyzing a graph to determine a first display device associated with a user, the graph comprising: first nodes of a first node type; second nodes of a second node type; and a plurality of ownership edges connecting the first nodes and the second nodes, each particular ownership edge indicating that a particular user corresponding to a particular first node owns a particular display device corresponding to a particular second node; by the one or more computer systems, providing information to display a channel switching interface on the first display device of the user, the channel switching interface operable to permit the user to select particular media content to view on a second display device; and by the one or more computer systems, in response to receiving a selection by the user within the channel switching interface of particular media content, providing one or more instructions to display the particular media content on the second display device.
|
1. A method comprising: by one or more computer systems, analyzing a graph to determine a first display device associated with a user, the graph comprising: first nodes of a first node type; second nodes of a second node type; and a plurality of ownership edges connecting the first nodes and the second nodes, each particular ownership edge indicating that a particular user corresponding to a particular first node owns a particular display device corresponding to a particular second node; by the one or more computer systems, providing information to display a channel switching interface on the first display device of the user, the channel switching interface operable to permit the user to select particular media content to view on a second display device; and by the one or more computer systems, in response to receiving a selection by the user within the channel switching interface of particular media content, providing one or more instructions to display the particular media content on the second display device. 3. The method of claim 1 , wherein: the channel switching interface comprises a plurality of entries, each entry corresponding to respective media content; and each particular entry comprises a facepile, the facepile comprising images representing other users who are currently watching, planning to watch, or who have previously liked the media content of the particular entry.
| 0.508642 |
10. The system of claim 1 , wherein the inference at least one of predicts quality of the one or more objects of interest, predicts an adjustment of the context, or identifies one or more patterns based upon graphical properties of the one or more sub graphs.
|
10. The system of claim 1 , wherein the inference at least one of predicts quality of the one or more objects of interest, predicts an adjustment of the context, or identifies one or more patterns based upon graphical properties of the one or more sub graphs. 14. The system of claim 10 , wherein identifying a pattern comprises at least one of identifying clusters, loops, anomalies, linkage patterns, edge density, path length between nodes, and patterns matching or approximating stored reference patterns.
| 0.840655 |
12. A computer system comprising: one or more processors; a software program, executable on said computer system, the software program configured to: provide a code generation framework comprising an Application Program Interface (API) code generator element, a serializer code generator element, and a deserializer code generator element; and in response to the code generation framework receiving a model as an input, cause the API code generator element to parse the model and generate an API used to create, manipulate, save, and load a first model instance version in a first language comprising JavaScript or XSJS, cause the serializer code generator element to parse the model and generate serialization code used to create a second model instance version in a second language comprising XMI from the first model instance version, wherein the second model instance version is created by a follow-on application comprising a graphical model editor, and cause the deserializer code generator element to parse the model and generate deserialization code used to convert a model instance version in the second language into the first language, wherein the deserialization code comprises, a resource object having attached a string representation of the second model instance version, and a resource set object containing the resource object and an added resource of a referenced class element of another model, wherein the deserializer code generator element does not generate an object property from the enumeration literal that is a key word in the first language.
|
12. A computer system comprising: one or more processors; a software program, executable on said computer system, the software program configured to: provide a code generation framework comprising an Application Program Interface (API) code generator element, a serializer code generator element, and a deserializer code generator element; and in response to the code generation framework receiving a model as an input, cause the API code generator element to parse the model and generate an API used to create, manipulate, save, and load a first model instance version in a first language comprising JavaScript or XSJS, cause the serializer code generator element to parse the model and generate serialization code used to create a second model instance version in a second language comprising XMI from the first model instance version, wherein the second model instance version is created by a follow-on application comprising a graphical model editor, and cause the deserializer code generator element to parse the model and generate deserialization code used to convert a model instance version in the second language into the first language, wherein the deserialization code comprises, a resource object having attached a string representation of the second model instance version, and a resource set object containing the resource object and an added resource of a referenced class element of another model, wherein the deserializer code generator element does not generate an object property from the enumeration literal that is a key word in the first language. 13. The computer system as in claim 12 wherein the model instance version in the second language comprises the second model instance version.
| 0.651163 |
1. A system for processing and presenting web content comprising: a hardware network interface configured to receive web content from one or more web content providers, the web content including text-based content; a processor; and a computer-readable storage medium storing instructions executable by the processor to: extract the text-based content from the web content; parse the web content to extract the text-based content with a web content processing module by applying a different parsing strategy for each particular content provider associated with the web content, each parsing strategy being configured to filter and extract text-based content from an associated content provider for that parsing strategy based on a web document structure unique to the associated content provider; select and retrieve a template document for encoding the text-based content based on one or more of a type of the text-based content and a content provider that provided the text-based content, the template document including placeholders to be replaced with respective portions of the text-based content, a configuration of the template document and the placeholders of the template document being selected based on the type of the text-based content, where different template document configurations having one or more different placeholders from other template document configurations are selectively employed to encode different types of text-based content; and encode the text-based content to obtain encoded content that includes the text-based content with an encoding module using the retrieved template document, the retrieved template document being configured for the text-based content to encode and format the text-based content according to an encoding schema that is adapted for the type of the text-based content, and the encoded content having a format suitable for presenting the text-based content as spoken audio, the system further including a content database including one or more web text tables for storing each item of the text-based content in respective rows of the web text tables, and including a category table for storing available categories of text-based content in respective rows of the category table, where each web text table of the one or more web text tables is associated with a different type of web text stored in that web text table, and each web text table includes different fields from other web text tables based on the type of web text stored in that web text table.
|
1. A system for processing and presenting web content comprising: a hardware network interface configured to receive web content from one or more web content providers, the web content including text-based content; a processor; and a computer-readable storage medium storing instructions executable by the processor to: extract the text-based content from the web content; parse the web content to extract the text-based content with a web content processing module by applying a different parsing strategy for each particular content provider associated with the web content, each parsing strategy being configured to filter and extract text-based content from an associated content provider for that parsing strategy based on a web document structure unique to the associated content provider; select and retrieve a template document for encoding the text-based content based on one or more of a type of the text-based content and a content provider that provided the text-based content, the template document including placeholders to be replaced with respective portions of the text-based content, a configuration of the template document and the placeholders of the template document being selected based on the type of the text-based content, where different template document configurations having one or more different placeholders from other template document configurations are selectively employed to encode different types of text-based content; and encode the text-based content to obtain encoded content that includes the text-based content with an encoding module using the retrieved template document, the retrieved template document being configured for the text-based content to encode and format the text-based content according to an encoding schema that is adapted for the type of the text-based content, and the encoded content having a format suitable for presenting the text-based content as spoken audio, the system further including a content database including one or more web text tables for storing each item of the text-based content in respective rows of the web text tables, and including a category table for storing available categories of text-based content in respective rows of the category table, where each web text table of the one or more web text tables is associated with a different type of web text stored in that web text table, and each web text table includes different fields from other web text tables based on the type of web text stored in that web text table. 11. The system of claim 1 where, for each template document of a plurality of template documents, a database indicates one or more of a type of web text and a content provider associated with that template document, and where all text-based content having a type of web text or originating from a content provider is encoded via an encoding scheme from the template document associated with that type of web text or that content provider.
| 0.508026 |
1. A method for processing speech information in a speech recognition system, wherein the information is represented by a sequence of frames, said speech recognition system being capable of comparing a given frame set to a template, and having template memory to store said template, said processing method comprising the steps of: (a) combining contiguous acoustically similar frames of a previous frame set into representative frames to form a reduced template; (b) storing said reduced template in template memory; and (c) comparing frames of said given frame set to said representative frames of said reduced template according to the number of frames combined in said representative frames of said reduced template to produce a measure of similarity between the given frame set and the template.
|
1. A method for processing speech information in a speech recognition system, wherein the information is represented by a sequence of frames, said speech recognition system being capable of comparing a given frame set to a template, and having template memory to store said template, said processing method comprising the steps of: (a) combining contiguous acoustically similar frames of a previous frame set into representative frames to form a reduced template; (b) storing said reduced template in template memory; and (c) comparing frames of said given frame set to said representative frames of said reduced template according to the number of frames combined in said representative frames of said reduced template to produce a measure of similarity between the given frame set and the template. 7. The method of claim 1, wherein storing further includes the step of storing a first element of frame data corresponding to the difference between a second element of frame data and said first element of frame data.
| 0.611948 |
4. A method for automatically generating a knowledge base in a computer from a graphical representation of a logical tree having at least one non-disjunctive branch, comprising the steps of: a) verifying the organization of said logical tree; b) verifying the content of said logical tree; c) generating a plurality of global attributes; d) creating a plurality of classes; and e) creating a plurality of rules as defined by said tree using said plurality of global attributes and said plurality of classes, wherein said rules are executable by an inference engine in a backward chaining mode; wherein said step of verifying the content of said tree comprises the steps of: b1) verifying that a valid formula is associated with each said leg; b2) verifying that a valid test is associated with each said test node; b3) verifying that a valid solution is associated with each solution node; and b4) verifying that each link node in said logical tree is linked to either a procedure or to a domain.
|
4. A method for automatically generating a knowledge base in a computer from a graphical representation of a logical tree having at least one non-disjunctive branch, comprising the steps of: a) verifying the organization of said logical tree; b) verifying the content of said logical tree; c) generating a plurality of global attributes; d) creating a plurality of classes; and e) creating a plurality of rules as defined by said tree using said plurality of global attributes and said plurality of classes, wherein said rules are executable by an inference engine in a backward chaining mode; wherein said step of verifying the content of said tree comprises the steps of: b1) verifying that a valid formula is associated with each said leg; b2) verifying that a valid test is associated with each said test node; b3) verifying that a valid solution is associated with each solution node; and b4) verifying that each link node in said logical tree is linked to either a procedure or to a domain. 5. The method of claim 4 further including the step f) generating links to electronic documents referenced by said knowledge base.
| 0.856747 |
17. One or more non-transitory computer-readable media as recited in claim 15 , wherein the acoustic characteristic comprises a room impulse response (RIR) of the environment.
|
17. One or more non-transitory computer-readable media as recited in claim 15 , wherein the acoustic characteristic comprises a room impulse response (RIR) of the environment. 18. One or more non-transitory computer-readable media as recited in claim 17 , wherein measuring the RIR of the environment comprises: instructing a speaker to emit a second known sound within the environment; capturing sound of the second known sound that has been reflected by one or more surfaces within the environment; generating an audio signal based on the captured sound; and comparing the captured sound in the audio signal to the second known sound to determine a disparity there between, the RIR being based at least in part on the disparity.
| 0.850324 |
13. A fuzzy logic expert system for reasoning about data, comprising: (i)means for accessing the data; (ii) means for determining a type of the data from a group consisting of numeric, linguistic and a hybrid combination thereof; (iii) means for selecting a rule for firing based on the determined type of the data; (iv) means for obtaining fuzzy membership grades; (v) means for aggregating the fuzzy membership grades by invoking a parametric formulation; (vi) means for applying a compositional rule of inference parametrically to extract a consequent to obtain a fuzzy output; and (vii) means for defuzifying the fuzzy output.
|
13. A fuzzy logic expert system for reasoning about data, comprising: (i)means for accessing the data; (ii) means for determining a type of the data from a group consisting of numeric, linguistic and a hybrid combination thereof; (iii) means for selecting a rule for firing based on the determined type of the data; (iv) means for obtaining fuzzy membership grades; (v) means for aggregating the fuzzy membership grades by invoking a parametric formulation; (vi) means for applying a compositional rule of inference parametrically to extract a consequent to obtain a fuzzy output; and (vii) means for defuzifying the fuzzy output. 18. The expert system according to claim 13 , wherein the type of the data is hybrid, and wherein the rule has a singleton consequent.
| 0.592752 |
1. A method of processing a request from a client program, the method comprising: receiving a request for an application from a client program, wherein the client program is a modeling framework that enables applications to be developed; after receiving the request for the application from the client program, determining a first source code corresponding to the application, the first source code written in a first programming language, the first source code comprising code declaring at least a first object class that inherits from another object class; after the determining of the first source code corresponding to the application, compiling the first source code to generate a second source code in JavaScript, wherein the second source code is executable by the client program and usable in development of the applications to be developed; and executing the second source code using the client program, including: loading one or more classes identified in the second source code, loading one or more objects instantiated from the one or more classes, and partitioning, by a namespace manager of the client program, a namespace of the client program into at least a first namespace and a second namespace, wherein (1) a first class and a first object associated with the first programming language are loaded in the first namespace and (2) a second class and a second object associated with a JavaScript engine typically having a single global namespace are loaded in the second namespace.
|
1. A method of processing a request from a client program, the method comprising: receiving a request for an application from a client program, wherein the client program is a modeling framework that enables applications to be developed; after receiving the request for the application from the client program, determining a first source code corresponding to the application, the first source code written in a first programming language, the first source code comprising code declaring at least a first object class that inherits from another object class; after the determining of the first source code corresponding to the application, compiling the first source code to generate a second source code in JavaScript, wherein the second source code is executable by the client program and usable in development of the applications to be developed; and executing the second source code using the client program, including: loading one or more classes identified in the second source code, loading one or more objects instantiated from the one or more classes, and partitioning, by a namespace manager of the client program, a namespace of the client program into at least a first namespace and a second namespace, wherein (1) a first class and a first object associated with the first programming language are loaded in the first namespace and (2) a second class and a second object associated with a JavaScript engine typically having a single global namespace are loaded in the second namespace. 9. The method of claim 1 wherein the first source code declares an aspect class that is attached to the first object class and causes an aspect object to be instantiated and attached to an object instantiated from the first object class.
| 0.615466 |
11. A method for processing element nodes of an extensible-markup language (XML) script, the method comprising: adding a first stack frame to a stack, the first stack frame associated with a first element node of the XML script, the first element node having a first argument that is a current element node of the XML script, the first element node requiring evaluation of the first argument to evaluate the first element node; adding a current stack frame to the stack above the original stack frame, the current stack frame associated with the current element node; determining that a new element node of the XML script is a current argument of the current element node, the current element node requiring evaluation of the current argument to evaluate the current element node; exposing the first stack frame, including setting a pointer of the stack to point to an end of the first stack frame; evaluating the current argument, including: inserting a new stack frame associated with the new element node into the stack, the new stack frame being inserted above the first stack frame and below the current stack frame rather than above the current stack frame, to simplify relative referencing for evaluation of a subsequent nested argument; evaluating the current argument using the new stack frame; returning a result from evaluation of the current argument to the current element node; and removing the new stack frame from the stack after returning the result from evaluation of the current argument to the current element node and before removing the current stack frame; and repeating the determining, inserting, evaluating returning and removing steps until all the element nodes of the XML script are evaluated.
|
11. A method for processing element nodes of an extensible-markup language (XML) script, the method comprising: adding a first stack frame to a stack, the first stack frame associated with a first element node of the XML script, the first element node having a first argument that is a current element node of the XML script, the first element node requiring evaluation of the first argument to evaluate the first element node; adding a current stack frame to the stack above the original stack frame, the current stack frame associated with the current element node; determining that a new element node of the XML script is a current argument of the current element node, the current element node requiring evaluation of the current argument to evaluate the current element node; exposing the first stack frame, including setting a pointer of the stack to point to an end of the first stack frame; evaluating the current argument, including: inserting a new stack frame associated with the new element node into the stack, the new stack frame being inserted above the first stack frame and below the current stack frame rather than above the current stack frame, to simplify relative referencing for evaluation of a subsequent nested argument; evaluating the current argument using the new stack frame; returning a result from evaluation of the current argument to the current element node; and removing the new stack frame from the stack after returning the result from evaluation of the current argument to the current element node and before removing the current stack frame; and repeating the determining, inserting, evaluating returning and removing steps until all the element nodes of the XML script are evaluated. 15. A method as recited in claim 11 , wherein the first stack frame is associated with a built-in function, and the current stack frame and the new stack frame are each associated with a different user-defined function.
| 0.520779 |
2. The method set forth in claim 1 , wherein the method further comprises carrying out the speech session using the steps of: (a) receiving the speech input at the mobile device via a short range wireless connection; (b) identifying a cloud service associated with the primary session context or the ancillary session context; (c) sending a service request to the cloud service; (d) receiving the service result from the cloud service; (e) generating a speech response using the service result; and (f) sending the speech response as audio speech from the mobile device via the short range wireless connection.
|
2. The method set forth in claim 1 , wherein the method further comprises carrying out the speech session using the steps of: (a) receiving the speech input at the mobile device via a short range wireless connection; (b) identifying a cloud service associated with the primary session context or the ancillary session context; (c) sending a service request to the cloud service; (d) receiving the service result from the cloud service; (e) generating a speech response using the service result; and (f) sending the speech response as audio speech from the mobile device via the short range wireless connection. 5. The method set forth in claim 2 , wherein step (c) further comprises determining the service request using parameters supplied in the speech recognition result.
| 0.7942 |
1. A method for converting both a tabbed table in an XML format and a collapsible section in the XML format to forms configured for storage in a relational database and use by a web-based application, said method comprising: converting, by a processor of a computing device, unstructured rich text information to XML files in the XML format, wherein the unstructured rich text information comprises the tabbed table as unstructured rich text and the collapsible section as unstructured rich text, wherein the tabbed table is a first type of unstructured rich text information that is tabbed table specific, wherein the collapsible section is a second type of unstructured rich text information that is collapsible section specific, and wherein the XML files in the XML format comprise the tabbed table in the XML format and the collapsible section in the XML format; transforming, by the processor using a first reusable stylesheet that is specific to the first type of unstructured rich text information that is tabbed table specific, the tabbed table in the XML format to an XHTML format configured for storage in the relational database by creating a parent, table object, creating a body for the parent table object to form a container including cells for the tabbed table and creating children of the parent, table object to record information contents of the cells in the container; initiating, by the processor, storage of the tabbed table object, including the body of the parent table object and the children of the parent table object, in the XHTML format in the relational database; subsequently exporting, by the processor, the tabbed table, including the body of the parent table object and the children of the parent table object, in the XHMTL format from the relational database to the web-based application; transforming, by the processor using a second reusable stylesheet that is specific to the second type of unstructured rich text information that is collapsible section specific, the collapsible section in the XML format to an XHTML format configured for storage in the relational database by creating a parent, collapsed object and creating children of the parent, collapsed object to record information content of an uncollapsed form of the collapsed parent object; initiating, by the processor, storage of the collapsible section in the XHTML format in the relational database; and subsequently exporting, by the processor, the collapsible section in the XHMTL format from the relational database to the web-based application.
|
1. A method for converting both a tabbed table in an XML format and a collapsible section in the XML format to forms configured for storage in a relational database and use by a web-based application, said method comprising: converting, by a processor of a computing device, unstructured rich text information to XML files in the XML format, wherein the unstructured rich text information comprises the tabbed table as unstructured rich text and the collapsible section as unstructured rich text, wherein the tabbed table is a first type of unstructured rich text information that is tabbed table specific, wherein the collapsible section is a second type of unstructured rich text information that is collapsible section specific, and wherein the XML files in the XML format comprise the tabbed table in the XML format and the collapsible section in the XML format; transforming, by the processor using a first reusable stylesheet that is specific to the first type of unstructured rich text information that is tabbed table specific, the tabbed table in the XML format to an XHTML format configured for storage in the relational database by creating a parent, table object, creating a body for the parent table object to form a container including cells for the tabbed table and creating children of the parent, table object to record information contents of the cells in the container; initiating, by the processor, storage of the tabbed table object, including the body of the parent table object and the children of the parent table object, in the XHTML format in the relational database; subsequently exporting, by the processor, the tabbed table, including the body of the parent table object and the children of the parent table object, in the XHMTL format from the relational database to the web-based application; transforming, by the processor using a second reusable stylesheet that is specific to the second type of unstructured rich text information that is collapsible section specific, the collapsible section in the XML format to an XHTML format configured for storage in the relational database by creating a parent, collapsed object and creating children of the parent, collapsed object to record information content of an uncollapsed form of the collapsed parent object; initiating, by the processor, storage of the collapsible section in the XHTML format in the relational database; and subsequently exporting, by the processor, the collapsible section in the XHMTL format from the relational database to the web-based application. 7. The method of claim 1 , said method further comprising: specifying, by the processor, a first name of the first stylesheet in a first local environment variable of a local environment message tree; retrieving, by the processor, the first name of the first stylesheet from the first local environment variable to transform the tabbed table in the XML format to an XHTML format; specifying, by the processor, a second name of the second stylesheet in a second local environment variable of the local environment message tree; and retrieving, by the processor, the second name of the second stylesheet from the second local environment variable to transform the collapsible section in the XML format to an XHTML format.
| 0.741007 |
14. One or more hardware computer storage media storing instructions which, when executed by the at least one processing unit, cause the at least one processing unit to perform acts comprising: obtaining data indicating that authors in a social media system provided links to network content to other users of the social media system; ranking individual authors of the social media system according to their propensity to provide individual links to corresponding network content that becomes popular with the other users of the social media system based on statistical analysis of the data, the ranking comprising: defining author scores of the individual authors, defining document scores of the individual links determining corresponding chronological orders in which the individual authors of the social media system provided the individual links to the other users of the social media system, determining respective popularities of the individual links, updating the document scores using the author scores, the chronological orders in which the individual links were provided by the individual authors, and the respective popularities of the individual links to generate update document scores, and updating the author scores using the updated document scores, the chronological orders in which the individual links were provided by the individual authors, and the respective popularities of the individual links to generate updated author scores; and outputting a ranked list of the individual authors based on the updated author scores.
|
14. One or more hardware computer storage media storing instructions which, when executed by the at least one processing unit, cause the at least one processing unit to perform acts comprising: obtaining data indicating that authors in a social media system provided links to network content to other users of the social media system; ranking individual authors of the social media system according to their propensity to provide individual links to corresponding network content that becomes popular with the other users of the social media system based on statistical analysis of the data, the ranking comprising: defining author scores of the individual authors, defining document scores of the individual links determining corresponding chronological orders in which the individual authors of the social media system provided the individual links to the other users of the social media system, determining respective popularities of the individual links, updating the document scores using the author scores, the chronological orders in which the individual links were provided by the individual authors, and the respective popularities of the individual links to generate update document scores, and updating the author scores using the updated document scores, the chronological orders in which the individual links were provided by the individual authors, and the respective popularities of the individual links to generate updated author scores; and outputting a ranked list of the individual authors based on the updated author scores. 17. The one or more hardware computer storage media of claim 14 , the acts further comprising: updating the document scores and the author scores iteratively using a particular mathematical term.
| 0.54196 |
20. An article of manufacture comprising: a non-transitory machine-accessible storage medium storing data that, when accessed by a machine, cause the machine to perform operations comprising: analyzing a web page content for predetermined parameters, wherein at least one of the predetermined parameters is based on an image media content; generating a tag that encapsulates the at least one predetermined parameter; processing the web page content to provide text representing the web page content; inserting the tag into the text to provide tokens; inputting the tokens into a latent semantic mapping (LSM) filter; mapping the tokens into a vector space of the latent semantic mapping filter; analyzing the web page content using a latent semantic mapping filter, wherein the latent semantic mapping filter comprises a vector space containing a first plurality of vectors at a first location, and a second plurality of vectors at a second location, wherein the first location comprises materials related to predefined legitimate multimedia content, the second location comprises materials related to predefined explicit multimedia content, and wherein at least one input into the latent semantic mapping filter comprises one or more representations of the web page content that are mapped to a third location in a vector space; determining distances between the third location and the first location, and the third location and the second location; and determining whether to filter the web page content based on the distances.
|
20. An article of manufacture comprising: a non-transitory machine-accessible storage medium storing data that, when accessed by a machine, cause the machine to perform operations comprising: analyzing a web page content for predetermined parameters, wherein at least one of the predetermined parameters is based on an image media content; generating a tag that encapsulates the at least one predetermined parameter; processing the web page content to provide text representing the web page content; inserting the tag into the text to provide tokens; inputting the tokens into a latent semantic mapping (LSM) filter; mapping the tokens into a vector space of the latent semantic mapping filter; analyzing the web page content using a latent semantic mapping filter, wherein the latent semantic mapping filter comprises a vector space containing a first plurality of vectors at a first location, and a second plurality of vectors at a second location, wherein the first location comprises materials related to predefined legitimate multimedia content, the second location comprises materials related to predefined explicit multimedia content, and wherein at least one input into the latent semantic mapping filter comprises one or more representations of the web page content that are mapped to a third location in a vector space; determining distances between the third location and the first location, and the third location and the second location; and determining whether to filter the web page content based on the distances. 27. The article of manufacture of claim 20 , wherein the web page content includes an executable script from which text is extracted in processing the web page content.
| 0.526834 |
17. A method, comprising: defining favorite categories associated with a plurality of taxonomies prior to conducting a search of a database; creating a user profile, which includes interests of a user to succinctly provide a basis that defines the favorite categories and associating the favorite categories with the user profile such that the favorite categories are stored and are used subsequently in conducting a fast path search, wherein the favorite categories are recorded and automatically added to a list associated with the user; selecting a fast path searching option that allows the search of the database to be conducted as the fast path search in only the defined favorite categories; conducting the fast path search of the database located on a server using a displayed control to search the favorite categories, the fast path search being within a plurality of the favorite categories based upon search criteria by comparing the search criteria to content information within each favorite category of the favorite categories; retrieving and displaying search results associated with said each favorite category of the favorite categories which have matching criteria based on the conducted fast path search during the displaying of the favorite categories; allowing the user to conduct the fast path search of the database on the server for the plurality of the favorite categories in a single step for the content information obtained by the comparing, even when the favorite categories are from different taxonomies; using the server to define one or more common categories found within multiple searches as the favorite categories; prompting to the user to add one or more common categories found within one or more previous searches to the favorite categories; and displaying the favorite categories in an expanded manner to show sub categories of the favorite categories and to show the favorite categories in a hierarchical relationship; presenting an interface to the user allowing the user to specify selected ones of the taxonomies to expand by default.
|
17. A method, comprising: defining favorite categories associated with a plurality of taxonomies prior to conducting a search of a database; creating a user profile, which includes interests of a user to succinctly provide a basis that defines the favorite categories and associating the favorite categories with the user profile such that the favorite categories are stored and are used subsequently in conducting a fast path search, wherein the favorite categories are recorded and automatically added to a list associated with the user; selecting a fast path searching option that allows the search of the database to be conducted as the fast path search in only the defined favorite categories; conducting the fast path search of the database located on a server using a displayed control to search the favorite categories, the fast path search being within a plurality of the favorite categories based upon search criteria by comparing the search criteria to content information within each favorite category of the favorite categories; retrieving and displaying search results associated with said each favorite category of the favorite categories which have matching criteria based on the conducted fast path search during the displaying of the favorite categories; allowing the user to conduct the fast path search of the database on the server for the plurality of the favorite categories in a single step for the content information obtained by the comparing, even when the favorite categories are from different taxonomies; using the server to define one or more common categories found within multiple searches as the favorite categories; prompting to the user to add one or more common categories found within one or more previous searches to the favorite categories; and displaying the favorite categories in an expanded manner to show sub categories of the favorite categories and to show the favorite categories in a hierarchical relationship; presenting an interface to the user allowing the user to specify selected ones of the taxonomies to expand by default. 18. The method of claim 17 , wherein the favorite categories represent a categorization scheme.
| 0.639828 |
10. A system for defining and processing hardware description language (HDL) groups for use with an electronic circuit design to be fabricated comprising: a computing device having at least one processor configured to map one or more tool-specific objects into a group graph having one or more groups arranged as nodes in the group graph, wherein the group graph is configured as a data structure, wherein each of the one or more groups includes at least one sub-group, library information, and HDL design information, generate a search order associated with each of the one or more groups within the group graph and wherein the search order is determined, based upon, at least in part, a command line structure, wherein the search order associated with each of the one or more groups is based upon, at least in part, a hierarchical design configuration of the group graph, identify one or more undefined references from within a first group of the one or more groups within the group graph, bind one or more defined references from within the first group to one or more electronic circuit design components, and identify the one or more undefined references from within a second group of the one or more groups within the group graph, wherein the second group is selected based upon, at least in part, the one or more undefined references and the search order associated with the first group of the one or more groups.
|
10. A system for defining and processing hardware description language (HDL) groups for use with an electronic circuit design to be fabricated comprising: a computing device having at least one processor configured to map one or more tool-specific objects into a group graph having one or more groups arranged as nodes in the group graph, wherein the group graph is configured as a data structure, wherein each of the one or more groups includes at least one sub-group, library information, and HDL design information, generate a search order associated with each of the one or more groups within the group graph and wherein the search order is determined, based upon, at least in part, a command line structure, wherein the search order associated with each of the one or more groups is based upon, at least in part, a hierarchical design configuration of the group graph, identify one or more undefined references from within a first group of the one or more groups within the group graph, bind one or more defined references from within the first group to one or more electronic circuit design components, and identify the one or more undefined references from within a second group of the one or more groups within the group graph, wherein the second group is selected based upon, at least in part, the one or more undefined references and the search order associated with the first group of the one or more groups. 15. The system of claim 10 , wherein the at least one processor is further configured to iteratively acquire each of the one or more groups partially concurrently with the identification of one or more undefined references from the one or more references.
| 0.546914 |
14. A computer readable medium storing a computer program comprising: computer readable code for receiving a user utterance at the telematics unit from a user, the user utterance including a plurality of segments including a user pause between each segment, each of the plurality of segments having a plurality of words and a plurality of user pauses between the words; computer readable code for parsing the user utterance into a plurality of phonemes; computer readable code for forming a data string in which each user pause is associated with a phoneme adjacent to the user pause, wherein the computer readable code for forming the data string includes i) computer readable code for determining an average duration of each pause between the plurality of words in each segment, ii) computer readable code for assigning a time duration for each of the user pauses based on the average duration determination of each user pause between the plurality of words, iii) computer readable code for determining an average duration of each user pause between each segment, iv) computer readable code for assigning a time duration for each of the user pauses based on the average duration determination of each user pause between each segment, v) computer readable code for associating each pause with the phoneme adjacent to the user pause, and vi) computer readable code for concatenating each user pause and the associated phoneme, each user pause including its associated assigned time duration; computer readable code for generating a virtual utterance corresponding to the data string; and computer readable code for playing back the virtual utterance to the user.
|
14. A computer readable medium storing a computer program comprising: computer readable code for receiving a user utterance at the telematics unit from a user, the user utterance including a plurality of segments including a user pause between each segment, each of the plurality of segments having a plurality of words and a plurality of user pauses between the words; computer readable code for parsing the user utterance into a plurality of phonemes; computer readable code for forming a data string in which each user pause is associated with a phoneme adjacent to the user pause, wherein the computer readable code for forming the data string includes i) computer readable code for determining an average duration of each pause between the plurality of words in each segment, ii) computer readable code for assigning a time duration for each of the user pauses based on the average duration determination of each user pause between the plurality of words, iii) computer readable code for determining an average duration of each user pause between each segment, iv) computer readable code for assigning a time duration for each of the user pauses based on the average duration determination of each user pause between each segment, v) computer readable code for associating each pause with the phoneme adjacent to the user pause, and vi) computer readable code for concatenating each user pause and the associated phoneme, each user pause including its associated assigned time duration; computer readable code for generating a virtual utterance corresponding to the data string; and computer readable code for playing back the virtual utterance to the user. 17. The medium of claim 14 , further comprising: computer readable code for receiving a command from the user to perform an operation requiring playing back the virtual utterance; and computer readable code for retrieving the data string from a memory in the telematics unit for generating the virtual utterance for play back.
| 0.5 |
1. A method for creating a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data and calculations required for the business simulation and communication of information to provide a dynamic, goal based educational learning experience, comprising the steps of: (a) accessing the information in the spreadsheet object component of the rule-based expert system to retrieve indicia representative of a goal; (b) utilizing the information in the spreadsheet object component of the rule-based expert system to integrate examples into the business simulation to provide assistance with achieving the goal; (c) monitoring answers to questions posed to evaluate progress of a student toward the goal utilizing the spreadsheet object component of the rule-based expert system and providing dynamic, goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that further assists the student in accomplishing the goal; (d) analyzing the answers from the student utilizing system tools to compare the answers with a standard for achieving the goal; and (e) providing a linkage to a website of information to supplement the information stored in the spreadsheet object component to assist with achieving the goal.
|
1. A method for creating a business simulation utilizing a rule-based expert system with a spreadsheet object component that includes data and calculations required for the business simulation and communication of information to provide a dynamic, goal based educational learning experience, comprising the steps of: (a) accessing the information in the spreadsheet object component of the rule-based expert system to retrieve indicia representative of a goal; (b) utilizing the information in the spreadsheet object component of the rule-based expert system to integrate examples into the business simulation to provide assistance with achieving the goal; (c) monitoring answers to questions posed to evaluate progress of a student toward the goal utilizing the spreadsheet object component of the rule-based expert system and providing dynamic, goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that further assists the student in accomplishing the goal; (d) analyzing the answers from the student utilizing system tools to compare the answers with a standard for achieving the goal; and (e) providing a linkage to a website of information to supplement the information stored in the spreadsheet object component to assist with achieving the goal. 6. A method for creating a business simulation as recited in claim 1, wherein the website includes navigation information for the business simulation.
| 0.812189 |
28. An apparatus comprising a computer-readable medium tangibly storing instructions executable by a computer processor to perform a method comprising: (A) deriving, from a region of a document and a corresponding region of a spoken audio stream, a likelihood score representing a likelihood that the region of the document correctly represents content in the corresponding region of the spoken audio stream; (B) selecting a relevance score representing a measure of relevance of the region of the spoken audio stream, the measure of relevance representing a measure of importance that the region of the spoken audio stream be brought to the attention of a human proofreader; and (C) deriving, by dividing the relevance score by the likelihood score, an emphasis factor for modifying emphasis placed on the region of the spoken audio stream when played back.
|
28. An apparatus comprising a computer-readable medium tangibly storing instructions executable by a computer processor to perform a method comprising: (A) deriving, from a region of a document and a corresponding region of a spoken audio stream, a likelihood score representing a likelihood that the region of the document correctly represents content in the corresponding region of the spoken audio stream; (B) selecting a relevance score representing a measure of relevance of the region of the spoken audio stream, the measure of relevance representing a measure of importance that the region of the spoken audio stream be brought to the attention of a human proofreader; and (C) deriving, by dividing the relevance score by the likelihood score, an emphasis factor for modifying emphasis placed on the region of the spoken audio stream when played back. 32. The apparatus of claim 28 , wherein (C) comprises deriving, from the likelihood and the measure of relevance, a signal power adjustment factor for adjusting a signal power of the region of the spoken audio stream.
| 0.693508 |
8. A system comprising: a processor; and a memory device coupled to the processor, the memory device including instructions that, when executed by the processor, cause the processor to perform a method comprising: producing a lattice of object hypotheses based at least in part on a plurality of reference objects identified in an image corresponding to a geographic location, wherein each of the plurality of reference objects is related to a physical object at the geographic location; receiving input speech information that includes a request for information associated with at least a first reference object of the plurality of reference objects; producing a lattice of speech hypotheses based on at least a first possible description included in the speech information; producing a lattice of scored semantic hypotheses based on at least the lattice of object hypotheses and the lattice of speech hypotheses; determining that a single semantic interpretation score of the lattice of scored semantic hypotheses exceeds a predetermined value; and providing requested information associated with the at least the first reference object of the plurality of reference objects.
|
8. A system comprising: a processor; and a memory device coupled to the processor, the memory device including instructions that, when executed by the processor, cause the processor to perform a method comprising: producing a lattice of object hypotheses based at least in part on a plurality of reference objects identified in an image corresponding to a geographic location, wherein each of the plurality of reference objects is related to a physical object at the geographic location; receiving input speech information that includes a request for information associated with at least a first reference object of the plurality of reference objects; producing a lattice of speech hypotheses based on at least a first possible description included in the speech information; producing a lattice of scored semantic hypotheses based on at least the lattice of object hypotheses and the lattice of speech hypotheses; determining that a single semantic interpretation score of the lattice of scored semantic hypotheses exceeds a predetermined value; and providing requested information associated with the at least the first reference object of the plurality of reference objects. 12. The system of claim 8 , wherein producing the lattice of scored semantic hypotheses based on at least the lattice of object hypotheses and the lattice of speech hypotheses includes producing the lattice of scored semantic hypotheses based on at least the lattice of object hypotheses, the lattice of speech hypotheses, and a finite state machine.
| 0.505361 |
5. A method of determining at least one dependency in a computer network, comprising: selecting an output channel and input channel in the computer network; fitting a first probabilistic model to a time modulated function for the output channel; fitting a second probabilistic model to the time modulated function for the output channel without including the input channel in the second probabilistic model; and comparing the first probabilistic model and the second probabilistic model to determine whether the output channel depends on the input channel.
|
5. A method of determining at least one dependency in a computer network, comprising: selecting an output channel and input channel in the computer network; fitting a first probabilistic model to a time modulated function for the output channel; fitting a second probabilistic model to the time modulated function for the output channel without including the input channel in the second probabilistic model; and comparing the first probabilistic model and the second probabilistic model to determine whether the output channel depends on the input channel. 8. The method of claim 5 , further comprising: selecting additional output channels; and for each additional output channel, fitting a third probabilistic model to the time modulated function for the additional output channel; fitting a fourth probabilistic model to the time modulated function for the additional output channel without including the input channel in the fourth probabilistic model; and comparing the third probabilistic model and the fourth probabilistic model to determine whether the additional output channel depends on the input channel.
| 0.5 |
1. A method of automated auditing an insurance agreement using a computer coupled to a database, said method comprising: providing the insurance agreement for determining whether the insurance agreement is in compliance with a standard; prompting an input of a first selection criteria including at least one attribute describing the insurance agreement, the first selection criteria identifying a type of insurance agreement to be audited including at least one of life insurance, health insurance, personal property insurance, business casualty insurance, key-man insurance, and board of director's liability insurance; receiving, at the computer, the first selection criteria inputted by a user; automatically retrieving a second selection criteria by the computer from the database, the second selection criteria including other attributes describing the insurance agreement, the second selection criteria based on the first selection criteria, the second selection criteria including at least a face value of the insurance agreement; automatically selecting by the computer a subset of questions from a plurality of questions stored within the database in accordance with the first and second selection criteria, the subset of questions associated with at least one of the attributes received by the computer describing the insurance agreement, at least one question of the subset of questions is assigned a question weight; organizing the subset of questions into a plurality of pre-assigned categories, wherein each question included within the plurality of questions is pre-assigned to a category based on subject matter of the associated question, the plurality of pre-assigned categories including at least one of coverage, compliance, pricing, risk selection, underwriting, and line of business, and at least one of the plurality of pre-assigned categories is assigned a category weight; presenting the subset of questions to the user; receiving answers to the subset of questions from the user; scoring, on the computer, the answers to generate an answer score for each of the answers received from the user and modifying the answer score in accordance with the category weight; generating a categorical score for each category associated with the subset of questions based on a plurality of answer scores; generating an overall score associated with the subset of questions based on a plurality of answer scores; comparing the generated categorical scores to corresponding categorical threshold scores to determine whether the insurance agreement is in compliance with the standard; and comparing the overall score to a corresponding threshold score to determine whether the insurance agreement is in compliance with the standard, wherein at least one question of the subset of questions is assigned a zero-weight value such that the answer to a zero-weight value question is not scored, wherein each question is associated with at least two answer options, and wherein an answer weight for each question varies between the at least two answer options.
|
1. A method of automated auditing an insurance agreement using a computer coupled to a database, said method comprising: providing the insurance agreement for determining whether the insurance agreement is in compliance with a standard; prompting an input of a first selection criteria including at least one attribute describing the insurance agreement, the first selection criteria identifying a type of insurance agreement to be audited including at least one of life insurance, health insurance, personal property insurance, business casualty insurance, key-man insurance, and board of director's liability insurance; receiving, at the computer, the first selection criteria inputted by a user; automatically retrieving a second selection criteria by the computer from the database, the second selection criteria including other attributes describing the insurance agreement, the second selection criteria based on the first selection criteria, the second selection criteria including at least a face value of the insurance agreement; automatically selecting by the computer a subset of questions from a plurality of questions stored within the database in accordance with the first and second selection criteria, the subset of questions associated with at least one of the attributes received by the computer describing the insurance agreement, at least one question of the subset of questions is assigned a question weight; organizing the subset of questions into a plurality of pre-assigned categories, wherein each question included within the plurality of questions is pre-assigned to a category based on subject matter of the associated question, the plurality of pre-assigned categories including at least one of coverage, compliance, pricing, risk selection, underwriting, and line of business, and at least one of the plurality of pre-assigned categories is assigned a category weight; presenting the subset of questions to the user; receiving answers to the subset of questions from the user; scoring, on the computer, the answers to generate an answer score for each of the answers received from the user and modifying the answer score in accordance with the category weight; generating a categorical score for each category associated with the subset of questions based on a plurality of answer scores; generating an overall score associated with the subset of questions based on a plurality of answer scores; comparing the generated categorical scores to corresponding categorical threshold scores to determine whether the insurance agreement is in compliance with the standard; and comparing the overall score to a corresponding threshold score to determine whether the insurance agreement is in compliance with the standard, wherein at least one question of the subset of questions is assigned a zero-weight value such that the answer to a zero-weight value question is not scored, wherein each question is associated with at least two answer options, and wherein an answer weight for each question varies between the at least two answer options. 2. The method of claim 1 , wherein receiving a first selection criteria further comprises: receiving the first selection criteria inputted by the user including audit type indicia indicating at least one of an audit type and an audit purpose.
| 0.542808 |
15. The system of claim 14 , wherein the scoring engine receives the weighted features from the feature extractor and the model from the model generation engine, the scoring engine comparing the weighted features to the model and scoring the content items for the user.
|
15. The system of claim 14 , wherein the scoring engine receives the weighted features from the feature extractor and the model from the model generation engine, the scoring engine comparing the weighted features to the model and scoring the content items for the user. 17. The system of claim 15 , wherein the scoring engine scores the content items by predicting at least one of a positive reaction and a negative reaction from the user.
| 0.921827 |
20. A method comprising: searching for qualifying occurrences of a query q consisting of at least one entity and at least one keyword from a database of linked documents, identifying entity tuples from the qualifying occurrences of the entity and keyword; for each instance of entity tuple q(t) in one document d of the documents, assigning a local score p(q(t)|d) based on a context of the entity in that document and an uncertainty value associated with extraction of the entity from that document; for each distinct entity tuple q(t), aggregating all the local scores thereof into a global score across the documents, based on respective weight p(d) assigned to each respective document d, as follow, p o ( q ( t ) ) = p ( q ( t ) | D ) = ∑ d ∈ D p ( d ) · p ( q ( t ) | d ) ; normalizing the aggregated score by statistically validating the significance of said score over the database; and outputting a relatively ranked listing of the normalized scores of at least a subset of the distinct entity tuples, to a storage or display device.
|
20. A method comprising: searching for qualifying occurrences of a query q consisting of at least one entity and at least one keyword from a database of linked documents, identifying entity tuples from the qualifying occurrences of the entity and keyword; for each instance of entity tuple q(t) in one document d of the documents, assigning a local score p(q(t)|d) based on a context of the entity in that document and an uncertainty value associated with extraction of the entity from that document; for each distinct entity tuple q(t), aggregating all the local scores thereof into a global score across the documents, based on respective weight p(d) assigned to each respective document d, as follow, p o ( q ( t ) ) = p ( q ( t ) | D ) = ∑ d ∈ D p ( d ) · p ( q ( t ) | d ) ; normalizing the aggregated score by statistically validating the significance of said score over the database; and outputting a relatively ranked listing of the normalized scores of at least a subset of the distinct entity tuples, to a storage or display device. 22. The method of claim 20 , wherein the local score assigning includes identifying a weighting factor based on an extraction probability of instances of the at least one entity in the entity tuple.
| 0.665699 |
1. A computer-implemented method for analyzing network activity, comprising: receiving a plurality of labeled access event items and unlabeled access event items from a computer network, each access event item pertaining to a connection made in the computer network between a first entity and a second entity; constructing a multi-class classifier model based on the labeled access event items; predicting labels for the unlabeled access event items using the multi-class classifier model; generating scores for each access event item to identify potential anomalies using feature-based analysis and graph-based analysis; ranking the access event items using the generated scores; presenting a list of candidate problematic access event items to a user in ranked order based on the generated scores; receiving one or more labels from the user to assign to the presented access event items; removing the access event items with user assigned labels from consideration as problematic access event items; updating the ranked list of candidate problematic access event items; presenting the user with the updated list of candidate problematic access event items; and successively removing accepted access event items identified by the user from consideration to reveal at least one potentially unacceptable access event item, if the at least one potentially unacceptable access event item is present.
|
1. A computer-implemented method for analyzing network activity, comprising: receiving a plurality of labeled access event items and unlabeled access event items from a computer network, each access event item pertaining to a connection made in the computer network between a first entity and a second entity; constructing a multi-class classifier model based on the labeled access event items; predicting labels for the unlabeled access event items using the multi-class classifier model; generating scores for each access event item to identify potential anomalies using feature-based analysis and graph-based analysis; ranking the access event items using the generated scores; presenting a list of candidate problematic access event items to a user in ranked order based on the generated scores; receiving one or more labels from the user to assign to the presented access event items; removing the access event items with user assigned labels from consideration as problematic access event items; updating the ranked list of candidate problematic access event items; presenting the user with the updated list of candidate problematic access event items; and successively removing accepted access event items identified by the user from consideration to reveal at least one potentially unacceptable access event item, if the at least one potentially unacceptable access event item is present. 5. The computer-implemented method of claim 1 , wherein the plurality of labeled access event items and unlabeled access event items is a collection of access event items formed by aggregating plural sub-collections of access event items, the sub-collections of access event items being collected over plural respective time intervals.
| 0.507842 |
11. A computer program product for generating an assent indication in a document approval and review function for collaborative document editing, the computer program product comprising: a computer usable medium having computer usable program code embodied therewith, the computer usable program code comprising: computer usable program code for loading a document for editing in a document editor; computer usable program code for determining a set of authors for the document; computer usable program code for modifying a file name of the document by appending an identity of each author in the determined set author to the file name of the document; and, computer usable program code for changing a visual appearance in the modified file name of an identity of the assenting author by removing the identity of the assenting author from the modified file name of the document resulting in leaving the identity of each author in the determined set of authors that has yet to assent to the publication of the document in the modified file name of the document responsive to one of the authors in the determined set of authors assenting to a publication of the document.
|
11. A computer program product for generating an assent indication in a document approval and review function for collaborative document editing, the computer program product comprising: a computer usable medium having computer usable program code embodied therewith, the computer usable program code comprising: computer usable program code for loading a document for editing in a document editor; computer usable program code for determining a set of authors for the document; computer usable program code for modifying a file name of the document by appending an identity of each author in the determined set author to the file name of the document; and, computer usable program code for changing a visual appearance in the modified file name of an identity of the assenting author by removing the identity of the assenting author from the modified file name of the document resulting in leaving the identity of each author in the determined set of authors that has yet to assent to the publication of the document in the modified file name of the document responsive to one of the authors in the determined set of authors assenting to a publication of the document. 15. The computer program product of claim 11 , further comprising computer usable program code for applying a tag to the file name indicating assent in response to one of the authors in the set assenting to a publication of the document.
| 0.599448 |
1. A method comprising: presenting a user interface on a display screen communicably coupled with a computing device that includes memory and a processor, the user interface displaying a graphical representation of a website that includes a plurality of webpages, the representation including a plurality of graphical webpage snapshots that each depicts a respective webpage associated with the website, the representation further including a plurality of graphical indicators that illustrate links between the plurality of webpages, the representation further including a plurality of active tag indicators that are each associated with a respective one of the webpages, each active tag indicator being associated with a respective portion of computer programming code that is configured to collect data from visitors to the associated webpage and included in the respective webpage with which the active tag indicator is associated, wherein the representation further includes a plurality of webpage analytics indicators that are each associated with a respective one of the webpages and are each associated and selectable with at least one of the associated webpage's active tag indicators, each of the webpage analytics indicators, upon selection, describing one or more characteristics of the collected data associated with the respective webpage and it's at least one active tag indicator; receiving user input indicating an editing action to be performed with respect to a first one of the computer programming code portions associated with a first one of the active tag indicators and its associated webpage and that will present an advertisement when the associated webpage in which the first computer programming code portion is included is loaded in a web browser, the editing action adding the first computer programming code portion to or removing the first computer programming code portion from the webpage, wherein the webpage analytics indicator that is associated with the first active tag indicator is configured to describe one or more characteristics of web traffic associated with the first active tag indicator based on traffic results obtained after the website is updated to reflect the editing action; and transmitting an update instruction message via a communications interface, the update instruction message including instructions for updating the website to reflect the editing action.
|
1. A method comprising: presenting a user interface on a display screen communicably coupled with a computing device that includes memory and a processor, the user interface displaying a graphical representation of a website that includes a plurality of webpages, the representation including a plurality of graphical webpage snapshots that each depicts a respective webpage associated with the website, the representation further including a plurality of graphical indicators that illustrate links between the plurality of webpages, the representation further including a plurality of active tag indicators that are each associated with a respective one of the webpages, each active tag indicator being associated with a respective portion of computer programming code that is configured to collect data from visitors to the associated webpage and included in the respective webpage with which the active tag indicator is associated, wherein the representation further includes a plurality of webpage analytics indicators that are each associated with a respective one of the webpages and are each associated and selectable with at least one of the associated webpage's active tag indicators, each of the webpage analytics indicators, upon selection, describing one or more characteristics of the collected data associated with the respective webpage and it's at least one active tag indicator; receiving user input indicating an editing action to be performed with respect to a first one of the computer programming code portions associated with a first one of the active tag indicators and its associated webpage and that will present an advertisement when the associated webpage in which the first computer programming code portion is included is loaded in a web browser, the editing action adding the first computer programming code portion to or removing the first computer programming code portion from the webpage, wherein the webpage analytics indicator that is associated with the first active tag indicator is configured to describe one or more characteristics of web traffic associated with the first active tag indicator based on traffic results obtained after the website is updated to reflect the editing action; and transmitting an update instruction message via a communications interface, the update instruction message including instructions for updating the website to reflect the editing action. 6. The method recited in claim 1 , wherein the representation includes information identifying a plurality of relationships between selected ones of the webpages, wherein the relationships include indicators for the links that specify whether each associated link is bidirectional or unidirectional or whether such associated link is a commonly traveled link.
| 0.568265 |
1. A scene information extraction apparatus comprising: a first acquisition unit configured to acquire a plurality of comment information items related to video content which defines scenes in a time-sequence manner, each of the plurality of comment information items including a comment, and a start time and an end time of the comment, the comment corresponding to a user who has viewed the video content; a division unit configured to divide the comment into words by morpheme analysis for each of the plurality of comment information items; a second acquisition unit configured to acquire an estimated value of each of the words, the estimated value indicating a degree of importance used at a time that a scene corresponding to a zone of the video content extracted; an addition unit configured to add the estimated value of each of the words for the words during a period of time ranging from the start time of the comment to the end time of the comment that contains a corresponding word included in the words, and to acquire estimated value distributions of the words; and an extraction unit configured to extract a start time and an end time of one scene included in the scenes and to be extracted from the video content, based on a shape of the estimated value distributions.
|
1. A scene information extraction apparatus comprising: a first acquisition unit configured to acquire a plurality of comment information items related to video content which defines scenes in a time-sequence manner, each of the plurality of comment information items including a comment, and a start time and an end time of the comment, the comment corresponding to a user who has viewed the video content; a division unit configured to divide the comment into words by morpheme analysis for each of the plurality of comment information items; a second acquisition unit configured to acquire an estimated value of each of the words, the estimated value indicating a degree of importance used at a time that a scene corresponding to a zone of the video content extracted; an addition unit configured to add the estimated value of each of the words for the words during a period of time ranging from the start time of the comment to the end time of the comment that contains a corresponding word included in the words, and to acquire estimated value distributions of the words; and an extraction unit configured to extract a start time and an end time of one scene included in the scenes and to be extracted from the video content, based on a shape of the estimated value distributions. 7. The apparatus according to claim 1 , wherein the second acquisition unit is configured to acquire the estimated value of each of the words, based on a character string length of the comment which contains each of the words, and number of words included in the comment which contains each of the words.
| 0.508351 |
9. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving speech recognition output associated with speech from a user; receiving an error model characterizing how automatic speech recognition transcription errors are made; generating guesses of a true transcription based on an error model-based algorithm, wherein the error model-based algorithm uses the error model and the speech recognition output; and generating, based on the guesses of the true transcription, a personalized user model associated with a user voiceprint of the user, wherein the generating of the personalized user model comprises iteratively guessing the true transcription until a threshold is met.
|
9. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: receiving speech recognition output associated with speech from a user; receiving an error model characterizing how automatic speech recognition transcription errors are made; generating guesses of a true transcription based on an error model-based algorithm, wherein the error model-based algorithm uses the error model and the speech recognition output; and generating, based on the guesses of the true transcription, a personalized user model associated with a user voiceprint of the user, wherein the generating of the personalized user model comprises iteratively guessing the true transcription until a threshold is met. 10. The system of claim 9 , wherein generating of the guesses further comprises repeating, until a threshold is met, steps comprising: guessing the true transcription from a current guess of the personalized user model, to yield a current guess of the true transcription; and guessing the personalized user model based on the current guess of the true transcription.
| 0.502801 |
6. A text locating system as described in claim 1 wherein: said system further includes cursor storing means for storing the location of a cursor, that is, a movable location in said body of text; said search string means includes means for adding each word which it receives from the recognition means to a search string; said string means includes means for searching from a current cursor position to one end of a specified portion of said body of text for the first occurrence of a sub-sequence of one or more words matching said search string in response to each addition of a vocabulary word to said search string; said system further includes means for setting said location stored in said cursor storing means to point to the sub-sequence of one or more words, if any, found by said string matching means in response to the addition of a word to said search string; said probability altering means has matching-context means which include: means for finding all sub-sequences of one or more words in the portion of text from the current cursor to said end of a specified portion of text which match the current search string; means for finding all of the words which immediately follow those sub-sequences; and means for altering the probability that said recognition means will select a given vocabulary word as a function of the frequency of occurrence of that vocabulary word as one of said immediately following words.
|
6. A text locating system as described in claim 1 wherein: said system further includes cursor storing means for storing the location of a cursor, that is, a movable location in said body of text; said search string means includes means for adding each word which it receives from the recognition means to a search string; said string means includes means for searching from a current cursor position to one end of a specified portion of said body of text for the first occurrence of a sub-sequence of one or more words matching said search string in response to each addition of a vocabulary word to said search string; said system further includes means for setting said location stored in said cursor storing means to point to the sub-sequence of one or more words, if any, found by said string matching means in response to the addition of a word to said search string; said probability altering means has matching-context means which include: means for finding all sub-sequences of one or more words in the portion of text from the current cursor to said end of a specified portion of text which match the current search string; means for finding all of the words which immediately follow those sub-sequences; and means for altering the probability that said recognition means will select a given vocabulary word as a function of the frequency of occurrence of that vocabulary word as one of said immediately following words. 7. A text locating system as described in claim 6 wherein said matching-context means includes means for indicating if the sub-sequence of one or more words found to be matching the search string by the matching means is the only sub-sequence of one or more words matching that search string in the portion of text extending from the current cursor to said end of a specified portion of text.
| 0.681403 |
24. The computing device of claim 14 , wherein the instructions, when executed, further cause the at least one processor to: after receiving the indication of the subsequent portion of the continuous gesture, receive an indication of a third portion of the continuous gesture; determine, based only on the third portion of the continuous gesture, a word in the language model; after omitting the one or more characters from the text input field of the graphical user interface, output, for display at the text input field of the graphical user interface, the word.
|
24. The computing device of claim 14 , wherein the instructions, when executed, further cause the at least one processor to: after receiving the indication of the subsequent portion of the continuous gesture, receive an indication of a third portion of the continuous gesture; determine, based only on the third portion of the continuous gesture, a word in the language model; after omitting the one or more characters from the text input field of the graphical user interface, output, for display at the text input field of the graphical user interface, the word. 25. The computing device of claim 24 , wherein the continuous gesture is a single gesture continuously being detected by the presence-sensitive display while the at least one processor receives the indications of initial portion of the continuous gesture, the subsequent portion of the continuous gesture, and the third portion of the continuous gesture.
| 0.848144 |
12. The computer program product of claim 11 , wherein the computer readable program further causes the computing device to: collect a set of supporting evidence passages for the final answer; use passage scorers to form a feature vector for each passage in the set of supporting evidence passages to form a set of feature vectors; and rank the set of supporting evidence passages for the final answer using the evidence collection multi-instance learned model to form a ranked set of supporting evidence passages.
|
12. The computer program product of claim 11 , wherein the computer readable program further causes the computing device to: collect a set of supporting evidence passages for the final answer; use passage scorers to form a feature vector for each passage in the set of supporting evidence passages to form a set of feature vectors; and rank the set of supporting evidence passages for the final answer using the evidence collection multi-instance learned model to form a ranked set of supporting evidence passages. 13. The computer program product of claim 12 , wherein presenting a final answer from the ranked set of answers comprises presenting at least one supporting evidence passage from the ranked set of supporting evidence passages with the final answer.
| 0.89246 |
9. A computer-readable storage medium comprising instructions that are executable and, responsive to executing the instructions, a computer: receives input to create a phonetic scheme, the phonetic scheme comprising one or more phonetic character combinations in a source language and one or more native characters in a destination language for each of the phonetic character combinations; stores the phonetic scheme in a format that can be transferred to another computer; translates a phonetic character combination into one or more native characters in the destination language using the phonetic scheme, the phonetic character combination being translated by a phonetic input application executed by the computer; and displays a selectable list of suggestions of one or more native characters in the destination language, the suggestions including the one or more native characters in the destination language, a plurality of phonetic equivalents to the phonetic character combination based on the phonetic scheme, and a plurality of sound-alike equivalents to the one or more native characters in the destination language.
|
9. A computer-readable storage medium comprising instructions that are executable and, responsive to executing the instructions, a computer: receives input to create a phonetic scheme, the phonetic scheme comprising one or more phonetic character combinations in a source language and one or more native characters in a destination language for each of the phonetic character combinations; stores the phonetic scheme in a format that can be transferred to another computer; translates a phonetic character combination into one or more native characters in the destination language using the phonetic scheme, the phonetic character combination being translated by a phonetic input application executed by the computer; and displays a selectable list of suggestions of one or more native characters in the destination language, the suggestions including the one or more native characters in the destination language, a plurality of phonetic equivalents to the phonetic character combination based on the phonetic scheme, and a plurality of sound-alike equivalents to the one or more native characters in the destination language. 16. The computer-readable storage medium of claim 9 , further comprising additional instructions that are executable and, responsive to executing the additional instructions, the computer creates a dynamic help file to document the phonetic scheme created by a user.
| 0.547872 |
1. A computer-implemented method of ranking replacement target strings for a misspelled source string, the computer-implemented method comprising: converting the misspelled source string into a source phoneme sequence using a letter-to-sound system; utilizing a computer processor that is a component of the computer to traverse at least one phoneme-based trie structure so as to select a plurality of different candidate phoneme sequences based on a comparison of phonemes in the phoneme-based trie structure to the source phoneme sequence but without doing a direct comparison of every component of the plurality of different candidate phoneme sequences to a component of the source phoneme sequence; generating a count for each different candidate phoneme sequence in said plurality of different candidate phoneme sequences, the count being indicative of a quantity of edit operations required to transform the candidate phoneme sequence into the source phoneme sequence; utilizing the computer processor to select a limited number of the plurality of different candidate phoneme sequences based at least in part on said counts, the limited number being less than all of the different candidate phoneme sequences included in said plurality of different candidate phoneme sequences; utilizing the computer processor to select a first set of replacement target strings, each replacement target string in the first set being selected based on direct correspondence to a candidate phoneme sequences in said limited number of different candidate phoneme sequences; utilizing the computer processor to traverse at least one letter-based trie structure so as to select a plurality of different candidate letter sequences, wherein selecting the plurality of different candidate letter sequences comprises traversing the letter-based trie structure so as to identify the plurality of different candidate letter sequences without doing a direct comparison of every component of the plurality of different candidate letter sequences with every component of the misspelled source string; utilizing the computer processor to select a limited number of the plurality of different candidate letter sequences based at least in part on a count of a quantity of edit operations required to transform each different candidate letter sequence included in the limited number of different candidate letter sequences into the misspelled source string, the limited number of different candidate letter sequences being less than all of the different candidate letter sequences included in said plurality of different candidate letter sequences; utilizing the computer processor to select a second set of replacement target strings, each replacement target string in the second set being one of the candidate letter sequences in said limited number of the plurality of different candidate letter sequences; and utilizing the computer processor to rank the replacement strings in the first and/or second sets based on a summation of the count of the quantity of edit operations required to transform a particular different candidate phoneme sequence included in the limited number of the plurality of different candidate phoneme sequences into the source phoneme sequence plus the count of the quantity of edit operations required to transform a particular different candidate letter sequence included in the limited number of the plurality of different candidate letter sequences into the misspelled source string.
|
1. A computer-implemented method of ranking replacement target strings for a misspelled source string, the computer-implemented method comprising: converting the misspelled source string into a source phoneme sequence using a letter-to-sound system; utilizing a computer processor that is a component of the computer to traverse at least one phoneme-based trie structure so as to select a plurality of different candidate phoneme sequences based on a comparison of phonemes in the phoneme-based trie structure to the source phoneme sequence but without doing a direct comparison of every component of the plurality of different candidate phoneme sequences to a component of the source phoneme sequence; generating a count for each different candidate phoneme sequence in said plurality of different candidate phoneme sequences, the count being indicative of a quantity of edit operations required to transform the candidate phoneme sequence into the source phoneme sequence; utilizing the computer processor to select a limited number of the plurality of different candidate phoneme sequences based at least in part on said counts, the limited number being less than all of the different candidate phoneme sequences included in said plurality of different candidate phoneme sequences; utilizing the computer processor to select a first set of replacement target strings, each replacement target string in the first set being selected based on direct correspondence to a candidate phoneme sequences in said limited number of different candidate phoneme sequences; utilizing the computer processor to traverse at least one letter-based trie structure so as to select a plurality of different candidate letter sequences, wherein selecting the plurality of different candidate letter sequences comprises traversing the letter-based trie structure so as to identify the plurality of different candidate letter sequences without doing a direct comparison of every component of the plurality of different candidate letter sequences with every component of the misspelled source string; utilizing the computer processor to select a limited number of the plurality of different candidate letter sequences based at least in part on a count of a quantity of edit operations required to transform each different candidate letter sequence included in the limited number of different candidate letter sequences into the misspelled source string, the limited number of different candidate letter sequences being less than all of the different candidate letter sequences included in said plurality of different candidate letter sequences; utilizing the computer processor to select a second set of replacement target strings, each replacement target string in the second set being one of the candidate letter sequences in said limited number of the plurality of different candidate letter sequences; and utilizing the computer processor to rank the replacement strings in the first and/or second sets based on a summation of the count of the quantity of edit operations required to transform a particular different candidate phoneme sequence included in the limited number of the plurality of different candidate phoneme sequences into the source phoneme sequence plus the count of the quantity of edit operations required to transform a particular different candidate letter sequence included in the limited number of the plurality of different candidate letter sequences into the misspelled source string. 2. The computer-implemented method of claim 1 , wherein the phoneme-based trie structure is derived from a lexicon that includes the first and second sets of replacement target strings.
| 0.559378 |
9. A computer implemented system comprising the following computer executable components: an association component that relates resources or entities based on an aggregate of user notions that are assigned to relationships, the association component incorporating an artificial intelligence component in conjunction with a training model to determine tagging trends via an automatic classifier system, a classifier in the automatic classifier system comprising a function that maps an input attribute vector x=(x1, x2, x3, x4, xn) to a confidence that an input belongs to a class comprising the function f(x)=confidence(class), wherein the entities comprise at least one of people, paper documents, static/dynamic web pages, files, emails, and multimedia files; a storage medium that stores the relationships; unique references that tie at least one of the resources or entities together, wherein the unique references comprise a plurality of links, the plurality of links appearing to users of the at least one of the resources or entities to be directly added to the at least one of the resources or entities, the plurality of links comprising at least one of data types, metadata, resource locations, and hash signatures, wherein at least one of the plurality of links is utilized to link at least two existing resources or entities based on user preferences, wherein the user preferences are independent of association preferences set by creators of the resources or entities; an inference component that infers relationships between the resources upon the resources being tagged as being relevant for a particular purpose, wherein the relationships are inferred by scoring at least one potential tagging trend from a list of potential tagging trends for auto suggestion to the users of the resources, wherein the scoring comprises assigning a point for each time one of the resources has been employed with a tagging trend, wherein the list of potential tagging trends is selected by employing a statistical analysis, the statistical analysis comprising a number of standard deviations away from a statistical mean, wherein resources more than two standard deviations away are employed for auto suggesting a tagging trend based on a collective user behavior, wherein a pseudo-hierarchy is created, based, at least in part, upon the tagged resources and user behavior relationships between the resources; a client component that performs tagging via metadata derived from the relationships, wherein the client component further: adds the metadata to the resources; connects into an external search system for performing a search with the metadata, wherein the metadata is exposed as fake web pages, the fake web pages comprising at least one list of tagged user Uniform Resource Locators (URLs), wherein the at least one list of tagged URLs is employed directly by the external search system; and enhances an inverted look up table via additional rows based on the metadata, the metadata implementing user notions regarding resource relationships; and a middle tier that implements logic involved to relate the resources or entities and infer states of the computer implemented system, an environment and a user from a set of observations captured via events and data, wherein an inference is employed to generate a probability distribution over the states to update previously inferred schema and tighten criteria on an inferring algorithm based upon a kind of data being processed.
|
9. A computer implemented system comprising the following computer executable components: an association component that relates resources or entities based on an aggregate of user notions that are assigned to relationships, the association component incorporating an artificial intelligence component in conjunction with a training model to determine tagging trends via an automatic classifier system, a classifier in the automatic classifier system comprising a function that maps an input attribute vector x=(x1, x2, x3, x4, xn) to a confidence that an input belongs to a class comprising the function f(x)=confidence(class), wherein the entities comprise at least one of people, paper documents, static/dynamic web pages, files, emails, and multimedia files; a storage medium that stores the relationships; unique references that tie at least one of the resources or entities together, wherein the unique references comprise a plurality of links, the plurality of links appearing to users of the at least one of the resources or entities to be directly added to the at least one of the resources or entities, the plurality of links comprising at least one of data types, metadata, resource locations, and hash signatures, wherein at least one of the plurality of links is utilized to link at least two existing resources or entities based on user preferences, wherein the user preferences are independent of association preferences set by creators of the resources or entities; an inference component that infers relationships between the resources upon the resources being tagged as being relevant for a particular purpose, wherein the relationships are inferred by scoring at least one potential tagging trend from a list of potential tagging trends for auto suggestion to the users of the resources, wherein the scoring comprises assigning a point for each time one of the resources has been employed with a tagging trend, wherein the list of potential tagging trends is selected by employing a statistical analysis, the statistical analysis comprising a number of standard deviations away from a statistical mean, wherein resources more than two standard deviations away are employed for auto suggesting a tagging trend based on a collective user behavior, wherein a pseudo-hierarchy is created, based, at least in part, upon the tagged resources and user behavior relationships between the resources; a client component that performs tagging via metadata derived from the relationships, wherein the client component further: adds the metadata to the resources; connects into an external search system for performing a search with the metadata, wherein the metadata is exposed as fake web pages, the fake web pages comprising at least one list of tagged user Uniform Resource Locators (URLs), wherein the at least one list of tagged URLs is employed directly by the external search system; and enhances an inverted look up table via additional rows based on the metadata, the metadata implementing user notions regarding resource relationships; and a middle tier that implements logic involved to relate the resources or entities and infer states of the computer implemented system, an environment and a user from a set of observations captured via events and data, wherein an inference is employed to generate a probability distribution over the states to update previously inferred schema and tighten criteria on an inferring algorithm based upon a kind of data being processed. 10. The computer implemented system of claim 9 , the aggregate of user notions further based on at least one of: machine learning; assigned notions; and inferred notions.
| 0.5 |
1. One or more non-transitory computer-readable media having instructions stored thereon which, when executed by a processor of a computing device, provide the computing device with a redaction module to: receive a request to redact a selection of a group of text from a document, wherein the group of text comprises one or more words; identify instances of the group of text occurring within the document, including for each instance of the group of text, word coordinate information of the one or more words of the instance, wherein the word coordinate information of the one or more words of the instance includes (x, y) coordinates of the one or more words; and generate redaction information for a redaction mask, including redaction coordinates, for each instance of the group of text, wherein the redaction coordinates of each redaction mask include (x, y) coordinates of the redaction mask, wherein generation of the (x, y) coordinates of a redaction mask is based at least in part on the (x, y) coordinates of the one or more words of the instance of the group of text to be redacted, wherein application of the redaction masks in accordance with the redaction coordinates of the redaction masks redacts the respective instances of the group of text, wherein a y-height of the mask is substantially equal to a height of a tallest letter within the respective instances of the group of text, wherein the height of the tallest letter is greater than heights of at least some of other letters within the respective instances of the group of text.
|
1. One or more non-transitory computer-readable media having instructions stored thereon which, when executed by a processor of a computing device, provide the computing device with a redaction module to: receive a request to redact a selection of a group of text from a document, wherein the group of text comprises one or more words; identify instances of the group of text occurring within the document, including for each instance of the group of text, word coordinate information of the one or more words of the instance, wherein the word coordinate information of the one or more words of the instance includes (x, y) coordinates of the one or more words; and generate redaction information for a redaction mask, including redaction coordinates, for each instance of the group of text, wherein the redaction coordinates of each redaction mask include (x, y) coordinates of the redaction mask, wherein generation of the (x, y) coordinates of a redaction mask is based at least in part on the (x, y) coordinates of the one or more words of the instance of the group of text to be redacted, wherein application of the redaction masks in accordance with the redaction coordinates of the redaction masks redacts the respective instances of the group of text, wherein a y-height of the mask is substantially equal to a height of a tallest letter within the respective instances of the group of text, wherein the height of the tallest letter is greater than heights of at least some of other letters within the respective instances of the group of text. 3. The one or more non-transitory computer-readable media of claim 1 , wherein application of the redaction masks in accordance with the redaction coordinates of the redaction masks redacts whitespace and punctuation occurring within the respective instances of the text.
| 0.592575 |
7. A translation result providing system, comprising: a memory in which at least one program is loaded; and at least one processor configured to execute the at least one program such that the at least one processor is configured to perform processes including, generating candidate sentences by translating a source sentence of a source language into a target language based on at least one of a rule-based machine translation model or a statistics-based machine translation model, classifying the candidate sentences into semantic categories, respectively, based on a condition related to attributes of the candidate sentences, the attributes including at least one of a writing style, a mood, a tense, or linguistic norm, and providing at least one of the classified candidate sentences as a translation result such that a first classified candidate translation sentence, from among the classified candidate translation sentences, which satisfies the condition is displayed in a first region of a screen and a second classified candidate translation sentence, from among the classified candidate translation sentences, which does not satisfy the condition is displayed in a second region of the screen visually distinguished from the first region of the screen.
|
7. A translation result providing system, comprising: a memory in which at least one program is loaded; and at least one processor configured to execute the at least one program such that the at least one processor is configured to perform processes including, generating candidate sentences by translating a source sentence of a source language into a target language based on at least one of a rule-based machine translation model or a statistics-based machine translation model, classifying the candidate sentences into semantic categories, respectively, based on a condition related to attributes of the candidate sentences, the attributes including at least one of a writing style, a mood, a tense, or linguistic norm, and providing at least one of the classified candidate sentences as a translation result such that a first classified candidate translation sentence, from among the classified candidate translation sentences, which satisfies the condition is displayed in a first region of a screen and a second classified candidate translation sentence, from among the classified candidate translation sentences, which does not satisfy the condition is displayed in a second region of the screen visually distinguished from the first region of the screen. 8. The translation result providing system of claim 7 , wherein: the classifying includes, sorting the candidate sentences translated in order of scores measured using a machine translation model, and extracting two or more of the candidate sentences having relatively high scores, and the providing includes displaying the extracted two or more of the candidate sentences as the translation result such that displaying one of the extracted two or more candidate sentences having highest scores is distinguished among the extracted two or more of the candidate sentences.
| 0.550228 |
1. A method comprising: receiving, via a first display device, a spoken content-based free-form natural language query to search content of a plurality of segments within a media presentation that has been processed for content-based searching, the media presentation comprising a series of slides; displaying, via the first display device, the media presentation, text from a speech recognition process applied to the spoken content-based free-form natural language query, and a scrollable search result set in response to the spoken content-based free-form natural language query, the scrollable search result set comprising a portion of the content of the plurality of segments which is associated with the spoken content-based free-form natural language query, while simultaneously transmitting the media presentation to a second display device for display at the second display device without the text and without the scrollable search result set; receiving, via the first display device, a selection from the scrollable search result set, to yield a selected segment of the plurality of segments, wherein the selection is based on a motion input; and transmitting the selected segment to the second display device for display at the second display device as part of the media presentation.
|
1. A method comprising: receiving, via a first display device, a spoken content-based free-form natural language query to search content of a plurality of segments within a media presentation that has been processed for content-based searching, the media presentation comprising a series of slides; displaying, via the first display device, the media presentation, text from a speech recognition process applied to the spoken content-based free-form natural language query, and a scrollable search result set in response to the spoken content-based free-form natural language query, the scrollable search result set comprising a portion of the content of the plurality of segments which is associated with the spoken content-based free-form natural language query, while simultaneously transmitting the media presentation to a second display device for display at the second display device without the text and without the scrollable search result set; receiving, via the first display device, a selection from the scrollable search result set, to yield a selected segment of the plurality of segments, wherein the selection is based on a motion input; and transmitting the selected segment to the second display device for display at the second display device as part of the media presentation. 4. The method of claim 1 , wherein the content comprises text associated with a segment of the plurality of segments.
| 0.566225 |
16. The computer readable medium of claim 15 , wherein the supplemental information for the verb variable text element comprises default information.
|
16. The computer readable medium of claim 15 , wherein the supplemental information for the verb variable text element comprises default information. 17. The computer readable medium of claim 16 , wherein the default information comprises masculine gender, singular count, first person speech, and normal faction.
| 0.916937 |
7. The method of claim 1 wherein providing to a multiplicity of users a presentation including content from a session document further comprises: providing a session document for the presentation, wherein the session document includes a session grammar and a session structured document; selecting from the session structured document a classified structural element in dependence upon user classifications of a user participant in the presentation; and presenting the selected structural element to the user.
|
7. The method of claim 1 wherein providing to a multiplicity of users a presentation including content from a session document further comprises: providing a session document for the presentation, wherein the session document includes a session grammar and a session structured document; selecting from the session structured document a classified structural element in dependence upon user classifications of a user participant in the presentation; and presenting the selected structural element to the user. 8. The method of claim 7 wherein selecting a classified structural element further comprises selecting a classified structural element having an associated classification identifier that corresponds to the user classification.
| 0.754717 |
31. An apparatus for highlighting and categorizing images from a document using a sequence of word tokens representing words of the document, the word tokens comprising character shape code classes, each word of the document being represented by only one word token, the apparatus comprising: means for eliminating predetermined character shape code classes from said sequence of word tokens; means for removing predetermined common function word tokens from said sequence of word tokens to form a reduced sequence of word tokens using a pattern matching technique and a stop token list; means for determining word token frequency appearance rates for the word tokens of the reduced sequence; means for ranking said frequency of appearance rates; means for determining nth or more most frequently appearing word tokens based on the ranked frequency of appearance rates; means for highlighting words of the document corresponding to the nth or more most frequently appearing word tokens; and means for categorizing the document into one of a plurality of pre-existing categories.
|
31. An apparatus for highlighting and categorizing images from a document using a sequence of word tokens representing words of the document, the word tokens comprising character shape code classes, each word of the document being represented by only one word token, the apparatus comprising: means for eliminating predetermined character shape code classes from said sequence of word tokens; means for removing predetermined common function word tokens from said sequence of word tokens to form a reduced sequence of word tokens using a pattern matching technique and a stop token list; means for determining word token frequency appearance rates for the word tokens of the reduced sequence; means for ranking said frequency of appearance rates; means for determining nth or more most frequently appearing word tokens based on the ranked frequency of appearance rates; means for highlighting words of the document corresponding to the nth or more most frequently appearing word tokens; and means for categorizing the document into one of a plurality of pre-existing categories. 33. The apparatus according to claim 31, wherein said means for removing comprises means for further removing numerical word tokens from said sequence of word tokens using an optional token list.
| 0.599291 |
20. A method for document processing for use in a computer system having a processor, storage and a display under control of the processor, the method comprising the steps of: (a) storing a plurality of model classes in the storage, each one of the plurality of model classes defining referencing data stored in the storage; (b) creating a container object to hold a plurality of objects instantiated from one or more of the plurality of model classes (c) creating logic for processing the data and objects held in the container object; (d) instantiating a root model object from one of the plurality of model classes, the root model object containing a reference to data of a first type; (e) instantiating a plurality of additional model objects from the plurality of model classes each one of the plurality of additional model objects containing a reference to data of a type different from the first type; (f) adding at least one of the additional model objects to a container in the root model object to provide a compound document from the root model object; and (g) processing the compound document by processing the root model object, which applies the processing to the at least one additional model object in the container in the root model object.
|
20. A method for document processing for use in a computer system having a processor, storage and a display under control of the processor, the method comprising the steps of: (a) storing a plurality of model classes in the storage, each one of the plurality of model classes defining referencing data stored in the storage; (b) creating a container object to hold a plurality of objects instantiated from one or more of the plurality of model classes (c) creating logic for processing the data and objects held in the container object; (d) instantiating a root model object from one of the plurality of model classes, the root model object containing a reference to data of a first type; (e) instantiating a plurality of additional model objects from the plurality of model classes each one of the plurality of additional model objects containing a reference to data of a type different from the first type; (f) adding at least one of the additional model objects to a container in the root model object to provide a compound document from the root model object; and (g) processing the compound document by processing the root model object, which applies the processing to the at least one additional model object in the container in the root model object. 30. The method of claim 20, including the step of supporting hierarchical document data including embedded data.
| 0.646175 |
1. A method performed by one or more computers, the method comprising: receiving, by the one or more computers, data indicating a candidate transcription for an utterance and a particular context for the utterance; obtaining, by the one or more computers, a maximum entropy language model that includes (i) scores for one or more n-gram features that each correspond to a respective n-gram and (ii) scores for one or more backoff features that each correspond to a set of n-grams for which there are no corresponding n-gram features in the maximum entropy language model; determining, by the one or more computers, based on the candidate transcription and the particular context, a feature value for (i) each of the one or more n-gram features of the maximum entropy language model and (ii) each of the one or more backoff features of the maximum entropy language model; inputting, by the one or more computers, the feature values for the n-gram features and the feature values for the backoff features to the maximum entropy language model; and receiving, by the one or more computers, from the maximum entropy language model, an output indicative of a likelihood of occurrence of the candidate transcription; selecting, by the one or more computers, based on the output of the maximum entropy language model, a transcription for the utterance from among a plurality of candidate transcriptions; and providing, by the one or more computers, the selected transcription to a client device.
|
1. A method performed by one or more computers, the method comprising: receiving, by the one or more computers, data indicating a candidate transcription for an utterance and a particular context for the utterance; obtaining, by the one or more computers, a maximum entropy language model that includes (i) scores for one or more n-gram features that each correspond to a respective n-gram and (ii) scores for one or more backoff features that each correspond to a set of n-grams for which there are no corresponding n-gram features in the maximum entropy language model; determining, by the one or more computers, based on the candidate transcription and the particular context, a feature value for (i) each of the one or more n-gram features of the maximum entropy language model and (ii) each of the one or more backoff features of the maximum entropy language model; inputting, by the one or more computers, the feature values for the n-gram features and the feature values for the backoff features to the maximum entropy language model; and receiving, by the one or more computers, from the maximum entropy language model, an output indicative of a likelihood of occurrence of the candidate transcription; selecting, by the one or more computers, based on the output of the maximum entropy language model, a transcription for the utterance from among a plurality of candidate transcriptions; and providing, by the one or more computers, the selected transcription to a client device. 8. The method of claim 1 , wherein generating the feature values for the one or more backoff features based on the particular context comprises generating at least one feature value that indicates that at least a portion of the particular context does not correspond to any of the n-gram features.
| 0.675703 |
6. The non-transitory computer readable media of claim 5 , wherein: each document in the group of documents is a page on a respective web site and the context of each respective context-specific translation model depends on the text of all the pages on the web site or the text of pages that are linked to directly or indirectly from the document.
|
6. The non-transitory computer readable media of claim 5 , wherein: each document in the group of documents is a page on a respective web site and the context of each respective context-specific translation model depends on the text of all the pages on the web site or the text of pages that are linked to directly or indirectly from the document. 7. The non-transitory computer readable media of claim 6 , wherein: the context of each respective context-specific translation model depends on the text of pages that link directly or indirectly to the document.
| 0.940735 |
10. The peer-to-peer network system as recited in claim 1 , wherein said plurality of peer services or content comprises a first service and a plurality of different implementations of said first service for different platform types.
|
10. The peer-to-peer network system as recited in claim 1 , wherein said plurality of peer services or content comprises a first service and a plurality of different implementations of said first service for different platform types. 11. The peer-to-peer network system as recited in claim 10 , further comprising a service class advertisement describing said first service and a service implementation advertisement for each implementation of said first service wherein each service implementation advertisement describes a corresponding one of said implementations of said first service.
| 0.894844 |
9. A device for parsing contents of an e-Form, the contents of said e-Form having been divided into more than one section with a different content identification code assigned to each said section of said e-Form, the device comprising a server comprising: a content identification code obtaining module configured to scan an e-Form submitted for processing to obtain said content identification codes, said content identification code obtaining module comprising a content identification code generating unit configured to generate a content identification code for a section lacking a content identification code, the content identification code for that section being generated based on the contents of that section; a determining module configured to determine, based on said content identification codes, which of said sections have a corresponding parsed result already in a cache module; a parsing module configured to parse contents of said sections without a parsed result already in said cache module; and a combining module configured to combine parsed results from said cache system with parsed results from parsing of sections without a parsed result already in said cache system.
|
9. A device for parsing contents of an e-Form, the contents of said e-Form having been divided into more than one section with a different content identification code assigned to each said section of said e-Form, the device comprising a server comprising: a content identification code obtaining module configured to scan an e-Form submitted for processing to obtain said content identification codes, said content identification code obtaining module comprising a content identification code generating unit configured to generate a content identification code for a section lacking a content identification code, the content identification code for that section being generated based on the contents of that section; a determining module configured to determine, based on said content identification codes, which of said sections have a corresponding parsed result already in a cache module; a parsing module configured to parse contents of said sections without a parsed result already in said cache module; and a combining module configured to combine parsed results from said cache system with parsed results from parsing of sections without a parsed result already in said cache system. 14. The device of claim 9 , in which the parsing module translates sections without a parsed result already in said cache module by translating said e-Form from eXtensible Forms Description Language (XFDL) to Dynamic Hyper Text Markup Language (DHTML).
| 0.532247 |
12. In a data processor which performs interactive processing, a help control system comprising: first means responsive to execution of commands in a user program for storing a history of changes in status of said user program; second means for storing rules for determining help messages to be displayed on the basis of said stored history of changes in status; third means for storing help messages to be displayed on the basis of said history of changes in status of said user program; fourth means for determining a help message according to the history of changes in status stored by said first means and said rules stored by said second means; and fifth means for displaying a help message determined by said fourth means.
|
12. In a data processor which performs interactive processing, a help control system comprising: first means responsive to execution of commands in a user program for storing a history of changes in status of said user program; second means for storing rules for determining help messages to be displayed on the basis of said stored history of changes in status; third means for storing help messages to be displayed on the basis of said history of changes in status of said user program; fourth means for determining a help message according to the history of changes in status stored by said first means and said rules stored by said second means; and fifth means for displaying a help message determined by said fourth means. 15. A help control system according to claim 12, wherein said rules of said second means can be changed by the said user program.
| 0.733607 |
1. A method for evaluating a conjunctive query, the method executed as a computer program by a general purpose computer, the conjunctive query comprising an at least one first predicate having variables; wherein the at least one first predicate is a relational predicate that is evaluated with a first engine using a relational database, and an at least one second predicate having variables, wherein the at least one second predicate is an external predicate that is evaluated using a second engine without using a relational database; the method comprising the steps of: defining the relational predicates as treated and defining the external predicates as non-treated; defining a variable (X) as distinguished if it appears as an argument in a treated predicate and it is a variable of an expression of a non-treated predicate; selecting a distinguished variable (X) from the conjunctive query, in absence of a distinguished variable by definition, choosing one of the variables in a non-treated predicate to serve as distinguished; forming a binding column (Bx) that contains a superset of values that are possible values of the selected distinguished variable (X) that fit limitations imposed by being an argument of the treated predicates; wherein said binding column (Bx) includes all possible values if it was chosen to serve as distinguished; evaluating the non-treated predicates having the selected distinguished variable (X) as a variable using the possible values from the binding column (Bx); updating the binding column (Bx) to be limited to the possible values fitting the evaluated non-treated predicates; marking the evaluated non-treated predicates as treated; repeating the steps for additionally chosen or selected distinguished variables, until resolving the query.
|
1. A method for evaluating a conjunctive query, the method executed as a computer program by a general purpose computer, the conjunctive query comprising an at least one first predicate having variables; wherein the at least one first predicate is a relational predicate that is evaluated with a first engine using a relational database, and an at least one second predicate having variables, wherein the at least one second predicate is an external predicate that is evaluated using a second engine without using a relational database; the method comprising the steps of: defining the relational predicates as treated and defining the external predicates as non-treated; defining a variable (X) as distinguished if it appears as an argument in a treated predicate and it is a variable of an expression of a non-treated predicate; selecting a distinguished variable (X) from the conjunctive query, in absence of a distinguished variable by definition, choosing one of the variables in a non-treated predicate to serve as distinguished; forming a binding column (Bx) that contains a superset of values that are possible values of the selected distinguished variable (X) that fit limitations imposed by being an argument of the treated predicates; wherein said binding column (Bx) includes all possible values if it was chosen to serve as distinguished; evaluating the non-treated predicates having the selected distinguished variable (X) as a variable using the possible values from the binding column (Bx); updating the binding column (Bx) to be limited to the possible values fitting the evaluated non-treated predicates; marking the evaluated non-treated predicates as treated; repeating the steps for additionally chosen or selected distinguished variables, until resolving the query. 8. The method of claim 1 wherein the first engine or the second engine are activated ad-hoc for evaluating the conjunctive query, or by a system providing the conjunctive query.
| 0.631879 |
1. A computer-implemented method comprising: receiving, from a user, a first portion of a personal name, the first portion comprising one or more characters of a first name, a nickname, a middle name or a last name; converting the first portion to a normalized portion of the personal name by reducing the one or more characters to their simplest equivalents; searching a main index to identify one or more first keys matching the normalized portion of the personal name; searching a phonetic index to identify one or more second keys matching the normalized portion of the personal name; compiling a first plurality of suggested matches, the first plurality of suggested matches comprising the union of indexed items corresponding to the one or more first keys and indexed items corresponding to the one or more second keys; and presenting, to the user, at least a portion of the first plurality of suggested matches.
|
1. A computer-implemented method comprising: receiving, from a user, a first portion of a personal name, the first portion comprising one or more characters of a first name, a nickname, a middle name or a last name; converting the first portion to a normalized portion of the personal name by reducing the one or more characters to their simplest equivalents; searching a main index to identify one or more first keys matching the normalized portion of the personal name; searching a phonetic index to identify one or more second keys matching the normalized portion of the personal name; compiling a first plurality of suggested matches, the first plurality of suggested matches comprising the union of indexed items corresponding to the one or more first keys and indexed items corresponding to the one or more second keys; and presenting, to the user, at least a portion of the first plurality of suggested matches. 2. The method of claim 1 , further comprising ranking the plurality of suggested matches according to a predicted relevance to the user.
| 0.620562 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.