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4. The method of claim 1 , further comprising: training the second machine translator, using the set of training data, to translate acceptable expressions for a value of the variable entity in the second natural language to corresponding canonical representations.
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4. The method of claim 1 , further comprising: training the second machine translator, using the set of training data, to translate acceptable expressions for a value of the variable entity in the second natural language to corresponding canonical representations. 5. The method of claim 4 , wherein the second machine translator receives information about the context of an acceptable expression for a value of the variable entity in the second language to be translated to a corresponding canonical representation and uses the context information to help translate the acceptable expression for the value of the variable entity in the second natural language to a corresponding canonical representation.
| 0.889418 |
32. A method of providing information to a user of a computerized apparatus, the method comprising: receiving via a network link a digitized representation of speech input, the representation generated via a speech recognition apparatus of the computerized apparatus, the input relating to an organization or entity which a user wishes to locate; based at least in part on the received representation, identifying a location associated with the organization or entity; and selecting and causing provision of a graphical or visual representation of the location via the network link, the graphical or visual representation being configured for display on a display device of the computerized apparatus and to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of the surroundings of the organization or entity; and causing display of advertising content that is contextually related to the organization or entity, contemporaneous with display of the graphical or visual representation, on the display device.
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32. A method of providing information to a user of a computerized apparatus, the method comprising: receiving via a network link a digitized representation of speech input, the representation generated via a speech recognition apparatus of the computerized apparatus, the input relating to an organization or entity which a user wishes to locate; based at least in part on the received representation, identifying a location associated with the organization or entity; and selecting and causing provision of a graphical or visual representation of the location via the network link, the graphical or visual representation being configured for display on a display device of the computerized apparatus and to aid a user in finding the organization or entity, the graphical or visual representation of the location also comprising a graphical or visual representation of the surroundings of the organization or entity; and causing display of advertising content that is contextually related to the organization or entity, contemporaneous with display of the graphical or visual representation, on the display device. 33. The method of claim 32 , wherein the advertising content is selected by one or more remote servers accessed via a network in data communication with a server performing said acts of receiving and identifying.
| 0.618594 |
1. A method of creating a template, the method comprising: identifying at least one domain ontology concept based on at least a portion of a first text-string input into a clinical document for a clinical indication; proposing, in the clinical document for the clinical indication, at least one name or label corresponding to the at least one domain ontology concept for selection by a user; inserting the at least one name or label corresponding to the at least one domain ontology concept into the clinical document for the clinical indication in response to selection of the at least one name or label by the user, the clinical document including documentation of at least clinical observations by a physician, the inserting the at least one name or label including auto-completing the first text string based on the identified at least one domain ontology concept and a context of the portion of the first text string in the clinical document; analyzing the clinical document to identify at least one first candidate for structural content in the clinical document, the at least one first candidate for structural content including a free form second text-string entry input into the clinical document by the user; obtaining at least one domain specific structural element associated with at least one further domain ontology concept corresponding to the identified at least one first candidate, the at least one domain specific structural element including the at least one first candidate and a plurality of second candidates, the plurality of second candidates being additional concepts identified as siblings of the at least one first candidate, wherein if the at least one first candidate exists in a library of existing domain specific structures, the obtaining step obtains the at least one domain specific structural element from the library of existing domain specific structures, and the plurality of second candidates are additional concepts identified as siblings of the at least one first candidate in the library of existing domain specific structures, and if the at least one first candidate does not exist in the library of existing domain specific structures, the obtaining step obtains the at least one domain specific structural element from a domain ontology database based on a parent node corresponding to the at least one first candidate; and creating a template corresponding to the clinical document by inserting, into the clinical document, structural content including the at least one domain specific structural element, the at least one domain specific structural element including the at least one candidate and the plurality of second candidates, wherein the structural content forms a structured part of the template for creating subsequent clinical documents for clinical indications, the plurality of second candidates are in the form of one or more third text-strings, and the at least one first candidate and the plurality of second candidates are displayed and selectable by the user for insertion into the subsequent clinical documents when creating the subsequent clinical documents from the created template.
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1. A method of creating a template, the method comprising: identifying at least one domain ontology concept based on at least a portion of a first text-string input into a clinical document for a clinical indication; proposing, in the clinical document for the clinical indication, at least one name or label corresponding to the at least one domain ontology concept for selection by a user; inserting the at least one name or label corresponding to the at least one domain ontology concept into the clinical document for the clinical indication in response to selection of the at least one name or label by the user, the clinical document including documentation of at least clinical observations by a physician, the inserting the at least one name or label including auto-completing the first text string based on the identified at least one domain ontology concept and a context of the portion of the first text string in the clinical document; analyzing the clinical document to identify at least one first candidate for structural content in the clinical document, the at least one first candidate for structural content including a free form second text-string entry input into the clinical document by the user; obtaining at least one domain specific structural element associated with at least one further domain ontology concept corresponding to the identified at least one first candidate, the at least one domain specific structural element including the at least one first candidate and a plurality of second candidates, the plurality of second candidates being additional concepts identified as siblings of the at least one first candidate, wherein if the at least one first candidate exists in a library of existing domain specific structures, the obtaining step obtains the at least one domain specific structural element from the library of existing domain specific structures, and the plurality of second candidates are additional concepts identified as siblings of the at least one first candidate in the library of existing domain specific structures, and if the at least one first candidate does not exist in the library of existing domain specific structures, the obtaining step obtains the at least one domain specific structural element from a domain ontology database based on a parent node corresponding to the at least one first candidate; and creating a template corresponding to the clinical document by inserting, into the clinical document, structural content including the at least one domain specific structural element, the at least one domain specific structural element including the at least one candidate and the plurality of second candidates, wherein the structural content forms a structured part of the template for creating subsequent clinical documents for clinical indications, the plurality of second candidates are in the form of one or more third text-strings, and the at least one first candidate and the plurality of second candidates are displayed and selectable by the user for insertion into the subsequent clinical documents when creating the subsequent clinical documents from the created template. 15. A non-transitory computer readable medium storing including program segments for, when executed on a computer device, causing the computer device to implement the method of claim 1 .
| 0.60728 |
31. A method as in claim 28 , wherein a step for creating a control file further comprises: i) by using a user interface for a spreadsheet loader, selecting the business object in an object tree section of the user interface, wherein the selection of the business object opens a list of attributes for the selected business object in an attributes tab section of the user interface; ii) dragging and dropping the attributes for the selected business object into columns of a spreadsheet data area of the user interface, the spreadsheet data area reflecting a spreadsheet dataset that is to be loaded by the spreadsheet loader; iii) using the drop and dragged attributes, mapping the columns into which the attributes were dragged to the business objects of the dragged attributes; iv) generating a control file reflecting the mapping step a)(iii).
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31. A method as in claim 28 , wherein a step for creating a control file further comprises: i) by using a user interface for a spreadsheet loader, selecting the business object in an object tree section of the user interface, wherein the selection of the business object opens a list of attributes for the selected business object in an attributes tab section of the user interface; ii) dragging and dropping the attributes for the selected business object into columns of a spreadsheet data area of the user interface, the spreadsheet data area reflecting a spreadsheet dataset that is to be loaded by the spreadsheet loader; iii) using the drop and dragged attributes, mapping the columns into which the attributes were dragged to the business objects of the dragged attributes; iv) generating a control file reflecting the mapping step a)(iii). 42. A method as in claim 31 , wherein the attributes in the attribute tab that are mandatory for the selected business object are distinguished from attributes that are not mandatory.
| 0.779582 |
1. A method comprising: receiving, by a computing system, a request from a client device for a target structured document; in response to the received request from the client device and in a first response phase: accessing, by the computing system, a data structure comprising an entry for the target structured document and one or more first resources associated with the target structured document; for each of one or more of the first resources associated with the target structured document: computing a probability for the first resource that represents a likelihood that the first resource will be included in a response to a future request for the target structured document; comparing the probability to a first predetermined threshold; and when the probability exceeds the first predetermined threshold, identifying the first resource as a selected first resource for the target structured document; generating, by the computing system, a first response portion comprising one or more of: one or more of the selected first resources; or one or more references to one or more of the selected first resources; sending, by the computing system, the first response portion to the client device; and further in response to the received request from the client device and in a second response phase taking place after sending the first response portion: for each of one or more second resources associated with the target structured document: computing a probability for the second resource that represents a likelihood that the second resource will be included in a response to a future request for the target structured document; comparing the probability to a second predetermined threshold; and when the probability exceeds the second predetermined threshold, identifying the second resource as a selected second resource for the target structured document; generating, by the computing system, a second response portion comprising structured document language code for the target structured document and one or more of: one or more of the selected second resources associated with the target structured document; or one or more references to one or more of the selected second resources; and sending, by the computing system, the second response portion to the same client device.
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1. A method comprising: receiving, by a computing system, a request from a client device for a target structured document; in response to the received request from the client device and in a first response phase: accessing, by the computing system, a data structure comprising an entry for the target structured document and one or more first resources associated with the target structured document; for each of one or more of the first resources associated with the target structured document: computing a probability for the first resource that represents a likelihood that the first resource will be included in a response to a future request for the target structured document; comparing the probability to a first predetermined threshold; and when the probability exceeds the first predetermined threshold, identifying the first resource as a selected first resource for the target structured document; generating, by the computing system, a first response portion comprising one or more of: one or more of the selected first resources; or one or more references to one or more of the selected first resources; sending, by the computing system, the first response portion to the client device; and further in response to the received request from the client device and in a second response phase taking place after sending the first response portion: for each of one or more second resources associated with the target structured document: computing a probability for the second resource that represents a likelihood that the second resource will be included in a response to a future request for the target structured document; comparing the probability to a second predetermined threshold; and when the probability exceeds the second predetermined threshold, identifying the second resource as a selected second resource for the target structured document; generating, by the computing system, a second response portion comprising structured document language code for the target structured document and one or more of: one or more of the selected second resources associated with the target structured document; or one or more references to one or more of the selected second resources; and sending, by the computing system, the second response portion to the same client device. 6. The method of claim 1 , wherein the first response portion and the second response portion are sent to the client device over a persistent network connection.
| 0.74 |
13. One or more non-transitory computer-readable storage media storing instructions which, when processed by one or more processors cause: receiving, from a user via a user interface of a first device, mapping input that specifies a particular gesture, one or more first device actions to associate with the particular gesture, and a first device context to associate with the particular gesture and the one or more first device actions, wherein the first device context includes one or more devices, other than the first device, are in the presence of the first device, or the one or more devices have logged in to a particular user account; storing, in a non-transitory storage medium, a first mapping that specifies the particular gesture, the first device context, and the one or more first device actions, wherein the non-transitory storage medium further stores a second mapping that specifies the particular gesture, a second device context, and one or more second device actions; detecting, by the first device, performance of a given gesture; in response to detecting performance of the given gesture: determining that the given gesture matches the particular gesture that is specified in the first mapping and the second mapping; in response to determining that the given gesture matches the particular gesture specified in the first mapping and the second mapping, reading the first mapping to determine the first device context that is specified in the first mapping and reading the second mapping to determine the second device context that is specified in the second mapping; determining whether one or more conditions external to the first device, detected by the first device, match the first device context; responsive to determining that the one or more conditions external to the first device match the first device context, causing the first device to perform the one or more first device actions that are specified in the first mapping; determining whether the one or more conditions external to the first device, detected by the first device, match the second device context; and responsive to determining that the one or more conditions external to the first device match the second device context, causing the first device to perform the one or more second device actions that are specified in the second mapping.
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13. One or more non-transitory computer-readable storage media storing instructions which, when processed by one or more processors cause: receiving, from a user via a user interface of a first device, mapping input that specifies a particular gesture, one or more first device actions to associate with the particular gesture, and a first device context to associate with the particular gesture and the one or more first device actions, wherein the first device context includes one or more devices, other than the first device, are in the presence of the first device, or the one or more devices have logged in to a particular user account; storing, in a non-transitory storage medium, a first mapping that specifies the particular gesture, the first device context, and the one or more first device actions, wherein the non-transitory storage medium further stores a second mapping that specifies the particular gesture, a second device context, and one or more second device actions; detecting, by the first device, performance of a given gesture; in response to detecting performance of the given gesture: determining that the given gesture matches the particular gesture that is specified in the first mapping and the second mapping; in response to determining that the given gesture matches the particular gesture specified in the first mapping and the second mapping, reading the first mapping to determine the first device context that is specified in the first mapping and reading the second mapping to determine the second device context that is specified in the second mapping; determining whether one or more conditions external to the first device, detected by the first device, match the first device context; responsive to determining that the one or more conditions external to the first device match the first device context, causing the first device to perform the one or more first device actions that are specified in the first mapping; determining whether the one or more conditions external to the first device, detected by the first device, match the second device context; and responsive to determining that the one or more conditions external to the first device match the second device context, causing the first device to perform the one or more second device actions that are specified in the second mapping. 19. The one or more non-transitory computer-readable storage media of claim 13 , wherein the one or more conditions external to the first device include that the one or more devices, other than the first device, are in the presence of the first device.
| 0.600132 |
14. A method in accordance with claim 1 wherein: the at least one communication is collected by an organization to which the person is affiliated; and the at least one communication is present on a system of the organization and is directed to or from the organization.
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14. A method in accordance with claim 1 wherein: the at least one communication is collected by an organization to which the person is affiliated; and the at least one communication is present on a system of the organization and is directed to or from the organization. 16. A method in accordance with claim 14 wherein: the output communication includes scoring pertaining to the risk posed by the person represented in the text.
| 0.822874 |
14. A string signature scanning system, the system comprising: a machine-readable storage device including a computer program; and one or more processors or one or more special purpose logic circuits operable to execute the computer program, and perform operations including providing one or more modules including: a signature pre-processing module operable to process one or more signatures into one or more formats including selecting one or more fingerprints for each fixed-size signature or each of one or more fixed-size signature substrings of each variable-size signature and constructing one or more search data structures for the one or more fingerprints associated with the one or more signatures and one or more follow-on search data structures, each successive fingerprint of a particular fixed-size signature or signature substring having a first basic unit in a scanning direction that is shifted one or more units from the previous fingerprint of the particular fixed-size signature or signature substrings such that the number of fingerprints for the particular fixed-size signature or signature substrings is equal to a step size for a signature scanning operation and the particular fixed-size signature or signature substring is identifiable at any location within any string fields to be scanned, where each fingerprint includes one or more fragments of a particular fixed-size signature or signature substring, the one or more fragments having particular locations anywhere within the particular fixed-size signature or signature substring; a fingerprint scan engine operable to identify one or more fingerprints associated with one or more signatures on an input string field, the identifying including scanning the input string field for the one or more fingerprints associated with the one or more signatures with either a zero or non-zero false positive rate using the one or more search data structures for the one or more fingerprints for each scan step size; a signature search engine operable to identify signatures for the identified fingerprints.
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14. A string signature scanning system, the system comprising: a machine-readable storage device including a computer program; and one or more processors or one or more special purpose logic circuits operable to execute the computer program, and perform operations including providing one or more modules including: a signature pre-processing module operable to process one or more signatures into one or more formats including selecting one or more fingerprints for each fixed-size signature or each of one or more fixed-size signature substrings of each variable-size signature and constructing one or more search data structures for the one or more fingerprints associated with the one or more signatures and one or more follow-on search data structures, each successive fingerprint of a particular fixed-size signature or signature substring having a first basic unit in a scanning direction that is shifted one or more units from the previous fingerprint of the particular fixed-size signature or signature substrings such that the number of fingerprints for the particular fixed-size signature or signature substrings is equal to a step size for a signature scanning operation and the particular fixed-size signature or signature substring is identifiable at any location within any string fields to be scanned, where each fingerprint includes one or more fragments of a particular fixed-size signature or signature substring, the one or more fragments having particular locations anywhere within the particular fixed-size signature or signature substring; a fingerprint scan engine operable to identify one or more fingerprints associated with one or more signatures on an input string field, the identifying including scanning the input string field for the one or more fingerprints associated with the one or more signatures with either a zero or non-zero false positive rate using the one or more search data structures for the one or more fingerprints for each scan step size; a signature search engine operable to identify signatures for the identified fingerprints. 21. The system of claim 14 , where the signature search engine includes a signature finder operable to identify any potential fixed-size string signatures on an input string field for one or more fixed-size string signatures associated with one or more identified fingerprints and a signature verifier operable to verify one or more potential fixed-size string signatures.
| 0.554245 |
19. An apparatus for processing a data stream associated with a given data stream application, comprising: a memory; and at least one processor coupled to the memory and configured to: obtain at least one range query associated with the data stream; and build a range query index based on the at least one range query using one or more virtual constructs such that the range query index is adaptive to one or more changes in a distribution of range query sizes; wherein building the range query index comprises decomposing the at least one range query into a minimal number of containment-encoded squares of varying sizes; and wherein the range query index is configured to process at least a portion of the data stream associated with the given data stream application.
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19. An apparatus for processing a data stream associated with a given data stream application, comprising: a memory; and at least one processor coupled to the memory and configured to: obtain at least one range query associated with the data stream; and build a range query index based on the at least one range query using one or more virtual constructs such that the range query index is adaptive to one or more changes in a distribution of range query sizes; wherein building the range query index comprises decomposing the at least one range query into a minimal number of containment-encoded squares of varying sizes; and wherein the range query index is configured to process at least a portion of the data stream associated with the given data stream application. 20. The apparatus of claim 19 , wherein building the range query index further comprises: dividing a monitoring region associated with the at least one range query into one or more initial-level virtual squares; defining one or more levels of virtual squares for each of the initial-level virtual squares; decomposing the at least one range query into one or more of the virtual squares; and associating an identifier of the at least one range query with the one or more decomposed virtual squares.
| 0.698651 |
9. A system of automated feature construction for algorithm portfolios in machine learning, comprising: one or more memory devices; one or more hardware processors operatively coupled to the memory device, one or more of the hardware processors operable to receive a problem instance represented as text describing a problem to be solved by computer-implemented problem solver, one or more of the hardware processors further operable to generate a gray scale image from the text by converting the text into the gray scale image that corresponds to the text, one or more of the hardware processors further operable to rescale the gray scale image to a predefined size that is smaller than an initial size of the gray scale image, into a rescaled gray scale image, the rescaled gray scale image representing features of the problem instance, one or more of the hardware processors operable to train based on the rescaled gray scale image as features, a machine learning-based convolutional neural network to learn to automatically determine one or more problem solvers from a portfolio of problem solvers suited for solving the problem instance, wherein the one or more of the hardware processors receives multiple problem instances, generates multiple gray scale images and rescales to multiple rescaled gray scale images respectively, the multiple rescaled gray scale images used as a training dataset for training the machine learning-based convolutional neural network.
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9. A system of automated feature construction for algorithm portfolios in machine learning, comprising: one or more memory devices; one or more hardware processors operatively coupled to the memory device, one or more of the hardware processors operable to receive a problem instance represented as text describing a problem to be solved by computer-implemented problem solver, one or more of the hardware processors further operable to generate a gray scale image from the text by converting the text into the gray scale image that corresponds to the text, one or more of the hardware processors further operable to rescale the gray scale image to a predefined size that is smaller than an initial size of the gray scale image, into a rescaled gray scale image, the rescaled gray scale image representing features of the problem instance, one or more of the hardware processors operable to train based on the rescaled gray scale image as features, a machine learning-based convolutional neural network to learn to automatically determine one or more problem solvers from a portfolio of problem solvers suited for solving the problem instance, wherein the one or more of the hardware processors receives multiple problem instances, generates multiple gray scale images and rescales to multiple rescaled gray scale images respectively, the multiple rescaled gray scale images used as a training dataset for training the machine learning-based convolutional neural network. 14. The system of claim 9 , wherein one or more of the hardware processors rescales by reshaping the gray scale image to a square gray scale image.
| 0.554896 |
1. A computerized method for analyzing verbal records to improve a textual transcript, the method comprising the steps of: identifying a training set and a test set of transcribed verbal records, the training set comprising a first subset of a plurality of transcribed verbal records, and the test set comprising a different second subset of the plurality of transcribed verbal records; for the each transcribed verbal record in the training set, determine a plurality of possible common phrases comprising a plurality of sequences of words appearing in the each verbal record in the training set, the each of the plurality of possible common phrases further having a minimum word length; for each of the plurality of possible common phrases, determine a best parameter; for each of the plurality of possible common phrases, finding a phrase accuracy based at least in part on a test for false positives; saving the best parameter for the each of the plurality of possible common phrases; and, applying the each of the plurality of possible common phrases to the transcribed verbal records, using the phrase accuracy, to create the textual transcript.
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1. A computerized method for analyzing verbal records to improve a textual transcript, the method comprising the steps of: identifying a training set and a test set of transcribed verbal records, the training set comprising a first subset of a plurality of transcribed verbal records, and the test set comprising a different second subset of the plurality of transcribed verbal records; for the each transcribed verbal record in the training set, determine a plurality of possible common phrases comprising a plurality of sequences of words appearing in the each verbal record in the training set, the each of the plurality of possible common phrases further having a minimum word length; for each of the plurality of possible common phrases, determine a best parameter; for each of the plurality of possible common phrases, finding a phrase accuracy based at least in part on a test for false positives; saving the best parameter for the each of the plurality of possible common phrases; and, applying the each of the plurality of possible common phrases to the transcribed verbal records, using the phrase accuracy, to create the textual transcript. 2. The method of claim 1 , wherein the plurality of sequences of words appears in a minimum percentage of the each verbal record in the training set.
| 0.692328 |
1. A computerized method for determining metadata associated with an electronic file, the method comprising: receiving, by a computing device, a filename including a first set of characters that represents a name for the electronic file, and a second set of additional characters, the second set of additional characters comprising: a first character representative of an event associated with the electronic file; and a second character representative of a custom action for the event; parsing, by the computing device, the filename to identify the second set of additional characters, wherein the second set of additional characters does not represent either a filename for a second file or a location of the second file; determining, by the computing device, metadata associated with the electronic file based on the second set of additional characters without downloading additional data of the electronic file, the metadata comprising: first metadata that defines an event associated with the electronic file from a first metadata element from a set of metadata elements that comprises the first character, wherein each metadata element in the set of metadata elements comprises a character and metadata associated with the character, and wherein the set of metadata elements is stored separately from the electronic file; and second metadata that defines a custom action for the event from a second metadata element from the set of metadata elements that comprises the second character, and the metadata element for each character from the second set of additional characters is different than metadata elements associated with remaining characters from the second set of additional characters; and processing, by the computing device, the electronic file based on the determined metadata, further comprising: receiving a request to execute an action for the electronic file; determining the request matches the event defined by the first metadata; determining the second metadata requires executing the custom action in addition to the requested action for the electronic file, wherein the custom action is different than the requested action; and executing both the requested action and the custom action for the electronic file.
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1. A computerized method for determining metadata associated with an electronic file, the method comprising: receiving, by a computing device, a filename including a first set of characters that represents a name for the electronic file, and a second set of additional characters, the second set of additional characters comprising: a first character representative of an event associated with the electronic file; and a second character representative of a custom action for the event; parsing, by the computing device, the filename to identify the second set of additional characters, wherein the second set of additional characters does not represent either a filename for a second file or a location of the second file; determining, by the computing device, metadata associated with the electronic file based on the second set of additional characters without downloading additional data of the electronic file, the metadata comprising: first metadata that defines an event associated with the electronic file from a first metadata element from a set of metadata elements that comprises the first character, wherein each metadata element in the set of metadata elements comprises a character and metadata associated with the character, and wherein the set of metadata elements is stored separately from the electronic file; and second metadata that defines a custom action for the event from a second metadata element from the set of metadata elements that comprises the second character, and the metadata element for each character from the second set of additional characters is different than metadata elements associated with remaining characters from the second set of additional characters; and processing, by the computing device, the electronic file based on the determined metadata, further comprising: receiving a request to execute an action for the electronic file; determining the request matches the event defined by the first metadata; determining the second metadata requires executing the custom action in addition to the requested action for the electronic file, wherein the custom action is different than the requested action; and executing both the requested action and the custom action for the electronic file. 3. The method of claim 1 , wherein determining the metadata comprises: parsing the second set of additional characters to determine a code; and retrieving metadata from a remote server using the code.
| 0.5 |
4. The method of claim 1 , wherein the indication of the next action comprises an indication of a transaction that is associated with the response message.
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4. The method of claim 1 , wherein the indication of the next action comprises an indication of a transaction that is associated with the response message. 5. The method of claim 4 , wherein the response message comprises an indication of a product or service, and wherein the transaction comprises a purchase of the product.
| 0.957222 |
14. The system of claim 1 , wherein said domain name appraisal module is further configured to calculate said pay-per-click value for said domain name by: i) receiving, from one or more pay-per-click bid metrics services or software, one or more pay-per-click bid metrics for said domain name; ii) generating a bid metric value comprising said one or more pay-per-click bid metrics; iii) receiving, from one or more search engines, a number of ads returned for said domain name as measured by said one or more search engines; and iv) generating a returned ads value comprising said number of ads returned for said domain name.
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14. The system of claim 1 , wherein said domain name appraisal module is further configured to calculate said pay-per-click value for said domain name by: i) receiving, from one or more pay-per-click bid metrics services or software, one or more pay-per-click bid metrics for said domain name; ii) generating a bid metric value comprising said one or more pay-per-click bid metrics; iii) receiving, from one or more search engines, a number of ads returned for said domain name as measured by said one or more search engines; and iv) generating a returned ads value comprising said number of ads returned for said domain name. 16. The system of claim 14 , wherein said domain name appraisal module is further configured to: i) write said bid metric value to a bid metric data field in a record for said domain name stored in a database communicatively coupled to said network; ii) write said returned ads value to a returned ads data field in said record; and iii) write said pay-per-click value to a pay-per-click data field in said record.
| 0.885654 |
10. The method of claim 5 , wherein determining the candidate score for each candidate group comprises: for each user in a candidate group, determining a product of an affinity between a user in the candidate group and the target user and a level of activity of the user; and summing the products.
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10. The method of claim 5 , wherein determining the candidate score for each candidate group comprises: for each user in a candidate group, determining a product of an affinity between a user in the candidate group and the target user and a level of activity of the user; and summing the products. 13. The method of claim 10 , wherein determining the candidate score for each candidate group further comprises: modifying candidate scores associated with candidate groups based on at least one of: characteristics of the target user and characteristics of users in the candidate groups.
| 0.839727 |
13. A process for supporting computer infrastructure, said process comprising automatically executable process software providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying a computer-readable code in a computing system, wherein the computer-readable code in combination with the computing system is capable of performing a method for searching a service registry system with a service name, the method comprising: receiving a request to locate, in a registry of the service registry system, a service description that corresponds to the service name specified in the request, wherein the registry comprises at least one service description searchable by a respective service identifier; subsequent to said receiving, determining that the service name specified in the request does not match any service identifier discovered in the registry; subsequent to said determining, parsing the service name into at least one component word; subsequent to said parsing, producing a respective synonym list for each component word of said at least one component word from a dictionary database of the service registry system, wherein the dictionary database comprises at least one record, wherein each record of said at least one record comprises a respective primary key and zero or more synonym of the primary key, wherein said producing comprising: composing a first database query that retrieves a first record from the dictionary database, wherein a primary key of the first record matches a first component word of said at least one component word; executing said composed first database query against the dictionary database; and storing the first record acquired as a result of said executing to a first synonym list corresponding to the first component word of the service name; subsequent to said producing, generating at least one candidate service name with said respective synonym list for each component word; subsequent to said generating, concluding that a first candidate service name of said at least one candidate service name is located in the registry by finding a first service identifier in the registry that is identical to the first candidate service name; and subsequent to said concluding, sending a first service description that corresponds to the first service identifier in the registry to an output device of the computer system upon which the service registry system operates.
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13. A process for supporting computer infrastructure, said process comprising automatically executable process software providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying a computer-readable code in a computing system, wherein the computer-readable code in combination with the computing system is capable of performing a method for searching a service registry system with a service name, the method comprising: receiving a request to locate, in a registry of the service registry system, a service description that corresponds to the service name specified in the request, wherein the registry comprises at least one service description searchable by a respective service identifier; subsequent to said receiving, determining that the service name specified in the request does not match any service identifier discovered in the registry; subsequent to said determining, parsing the service name into at least one component word; subsequent to said parsing, producing a respective synonym list for each component word of said at least one component word from a dictionary database of the service registry system, wherein the dictionary database comprises at least one record, wherein each record of said at least one record comprises a respective primary key and zero or more synonym of the primary key, wherein said producing comprising: composing a first database query that retrieves a first record from the dictionary database, wherein a primary key of the first record matches a first component word of said at least one component word; executing said composed first database query against the dictionary database; and storing the first record acquired as a result of said executing to a first synonym list corresponding to the first component word of the service name; subsequent to said producing, generating at least one candidate service name with said respective synonym list for each component word; subsequent to said generating, concluding that a first candidate service name of said at least one candidate service name is located in the registry by finding a first service identifier in the registry that is identical to the first candidate service name; and subsequent to said concluding, sending a first service description that corresponds to the first service identifier in the registry to an output device of the computer system upon which the service registry system operates. 16. The process of claim 13 , the method further comprising: repeating said concluding and said sending for each candidate service name of said at least one candidate service name from said generating.
| 0.555893 |
9. An apparatus for processing and debugging a hierarchically structured document, comprising: means for setting a break point at a line of the document; means for creating a data structure for keeping track of hierarchical levels of the document; means for inputting an element indicating a beginning of a first hierarchical level of the document; means for creating a plurality of references for an entry A in said data structure for keeping track of hierarchical levels, said plurality of references for the entry A being used to keep track of information of the first hierarchical level of the document including references used for keeping track of at least one of defined resources, declared resources, and dictionaries which are used during processing of the document; means for inputting an element at the first hierarchical level indicating that a first of said at least one of defined resources, declared resources, and dictionaries is to be used during processing of the document; means for changing at least one of the references for the entry A used for keeping track of information to refer to said first of said at least one of defined resources, declared resources, and dictionaries; means for inputting an element indicating a beginning of a second hierarchical level of the document which is below the first hierarchical level in the hierarchical structure of the document; means for creating a plurality of references for an entry B in said data structure for keeping track of hierarchical levels, the entry B being different from the entry A in said data structure for keeping track of hierarchical levels, said plurality of references for the entry B being used to keep track of information of the second hierarchical level of the document including references used for keeping track of at least one of defined resources, declared resources, and dictionaries which are used during processing of the document; means for inputting an element at the second hierarchical level indicating that a second of said at least one of defined resources, declared resources, and dictionaries is to be used during processing of the second hierarchical level, in addition to said first of said at least one of defined resources, declared resources, and dictionaries; means for changing the reference used for keeping track of said at least one of defined resources, declared resources, and dictionaries for the entry B to refer first to said second of said at least one of defined resources, declared resources, and dictionaries and subsequently to said first of said at least one of defined resources, declared resources, and dictionaries; means for accessing said at least one of defined resources, declared resources, and dictionaries by using first the reference to the second of said at least one of defined resources, declared resources, and dictionaries and if a desired parameter is not found, using subsequently the subsequent reference to the second of said at least one of defined resources, declared resources, and dictionaries, without referring to said plurality of references for the entry A; means for suspending processing of the document when said break point is processed; means for inputting a debugging command after processing has been suspended; and means for processing said debugging command.
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9. An apparatus for processing and debugging a hierarchically structured document, comprising: means for setting a break point at a line of the document; means for creating a data structure for keeping track of hierarchical levels of the document; means for inputting an element indicating a beginning of a first hierarchical level of the document; means for creating a plurality of references for an entry A in said data structure for keeping track of hierarchical levels, said plurality of references for the entry A being used to keep track of information of the first hierarchical level of the document including references used for keeping track of at least one of defined resources, declared resources, and dictionaries which are used during processing of the document; means for inputting an element at the first hierarchical level indicating that a first of said at least one of defined resources, declared resources, and dictionaries is to be used during processing of the document; means for changing at least one of the references for the entry A used for keeping track of information to refer to said first of said at least one of defined resources, declared resources, and dictionaries; means for inputting an element indicating a beginning of a second hierarchical level of the document which is below the first hierarchical level in the hierarchical structure of the document; means for creating a plurality of references for an entry B in said data structure for keeping track of hierarchical levels, the entry B being different from the entry A in said data structure for keeping track of hierarchical levels, said plurality of references for the entry B being used to keep track of information of the second hierarchical level of the document including references used for keeping track of at least one of defined resources, declared resources, and dictionaries which are used during processing of the document; means for inputting an element at the second hierarchical level indicating that a second of said at least one of defined resources, declared resources, and dictionaries is to be used during processing of the second hierarchical level, in addition to said first of said at least one of defined resources, declared resources, and dictionaries; means for changing the reference used for keeping track of said at least one of defined resources, declared resources, and dictionaries for the entry B to refer first to said second of said at least one of defined resources, declared resources, and dictionaries and subsequently to said first of said at least one of defined resources, declared resources, and dictionaries; means for accessing said at least one of defined resources, declared resources, and dictionaries by using first the reference to the second of said at least one of defined resources, declared resources, and dictionaries and if a desired parameter is not found, using subsequently the subsequent reference to the second of said at least one of defined resources, declared resources, and dictionaries, without referring to said plurality of references for the entry A; means for suspending processing of the document when said break point is processed; means for inputting a debugging command after processing has been suspended; and means for processing said debugging command. 10. An apparatus according to claim 9, wherein said means for setting a break point includes: means for inputting a line number from a user indicating where a break is to occur.
| 0.505357 |
13. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: identifying a genre of a content item being output by an electronic device based at least in part on an identity of a user associated with the electronic device, wherein the identity of the user is determined based at least in part on at least one of: a location of the electronic device; or demographic information of the user; receiving a request for information associated with a portion of the content item; selecting, based at least in part on the identified genre of the content item, a reference work entry from multiple different reference work entries each providing information pertinent to the request; and outputting the requested information from the selected reference work entry.
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13. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: identifying a genre of a content item being output by an electronic device based at least in part on an identity of a user associated with the electronic device, wherein the identity of the user is determined based at least in part on at least one of: a location of the electronic device; or demographic information of the user; receiving a request for information associated with a portion of the content item; selecting, based at least in part on the identified genre of the content item, a reference work entry from multiple different reference work entries each providing information pertinent to the request; and outputting the requested information from the selected reference work entry. 14. One or more non-transitory computer-readable media as recited in claim 13 , wherein the content item comprises audio, video, or text.
| 0.782168 |
11. The medium according to claim 10 , further comprising generating the additional phrase in accordance with a type of the detected ambiguity.
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11. The medium according to claim 10 , further comprising generating the additional phrase in accordance with a type of the detected ambiguity. 13. The medium according to claim 11 , wherein the generating the additional phrase determines the additional phrase based on at least one of the source language strings, the target language strings, a content type of the speech, a gender of a speaker, and age of the speaker.
| 0.915249 |
26. A method of configuring a complex event processing (CEP) system in which a stream of events is received via an event bus, each said event having a predefined event type, the method comprising: receiving queries that are to be executable in connection with the CEP system; determining, in connection with at least one processor, whether a received query either initially conforms to a CEP query language executable by an event processing agent, or must be translated from an enhanced query that conforms to a version of the CEP query language that has been enriched so that semantics thereof are represented in accordance with an ontology in order to render it executable via the event processing agent; when the received query must be translated, generating a translated query from the enhanced query in accordance with mappings between concepts of the CEP system and concepts of the ontology, wherein the enhanced query includes references to ontology concepts and the references to the ontology concepts are translated into queries processable by the event processing agent in accordance with the query language; and deploying all queries that initially conform to the CEP query language and all translated queries for possible subsequent execution; wherein the concepts of the ontology are classes, and wherein the generating of the translated query comprises, for the enhanced query: retrieving a class definition for all referenced classes from a corresponding ontology; determining whether the referenced classes are marked as being handled; when the referenced classes are marked as being handled, transforming the respective class definition to the query language, and compiling the translated query; and when the referenced classes are not marked as being handled: when the respective class does not have a corresponding mapping, replacing the class with a union of all of its sub-classes; when the respective class has a corresponding mapping but no sub-classes, removing the reference to the class; and when the respective class has a corresponding mapping and any sub-classes, adding a union with all sub-classes to the class and marking the class as handled.
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26. A method of configuring a complex event processing (CEP) system in which a stream of events is received via an event bus, each said event having a predefined event type, the method comprising: receiving queries that are to be executable in connection with the CEP system; determining, in connection with at least one processor, whether a received query either initially conforms to a CEP query language executable by an event processing agent, or must be translated from an enhanced query that conforms to a version of the CEP query language that has been enriched so that semantics thereof are represented in accordance with an ontology in order to render it executable via the event processing agent; when the received query must be translated, generating a translated query from the enhanced query in accordance with mappings between concepts of the CEP system and concepts of the ontology, wherein the enhanced query includes references to ontology concepts and the references to the ontology concepts are translated into queries processable by the event processing agent in accordance with the query language; and deploying all queries that initially conform to the CEP query language and all translated queries for possible subsequent execution; wherein the concepts of the ontology are classes, and wherein the generating of the translated query comprises, for the enhanced query: retrieving a class definition for all referenced classes from a corresponding ontology; determining whether the referenced classes are marked as being handled; when the referenced classes are marked as being handled, transforming the respective class definition to the query language, and compiling the translated query; and when the referenced classes are not marked as being handled: when the respective class does not have a corresponding mapping, replacing the class with a union of all of its sub-classes; when the respective class has a corresponding mapping but no sub-classes, removing the reference to the class; and when the respective class has a corresponding mapping and any sub-classes, adding a union with all sub-classes to the class and marking the class as handled. 28. The method of claim 26 , wherein concepts of the CEP query language include events, event types, and channels, and/or concepts of the ontology include classes.
| 0.600833 |
1. A computerized method for suggesting a product for purchase comprising the steps of: collecting, on a computer, coreference information from a web server serving web pages including a plurality of word groups, each of the word groups comprising a plurality of words, and describing a product in a group of products, the coreference information indicating coreferences in single web sessions of pairs of products in the group of products, the coreference information further indicating a number of a plurality of words across the group of products, a number of occurrences of each word for both coreferenced products of each pair of products, and a number of occurrences of each word for only one coreferenced product of each pair of products; calculating, on a computer, a score for each word of the plurality of words occurring in the plurality of word groups using the coreference information; selecting, on a computer, a subset of the plurality of words based at least in part on the score; performing, on a computer, a dimensionality reduction on the subset; and serving a web page from the web server, the web page including a description of a first product and a recommendation for a second product, the recommendation being based on a result from the performing step.
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1. A computerized method for suggesting a product for purchase comprising the steps of: collecting, on a computer, coreference information from a web server serving web pages including a plurality of word groups, each of the word groups comprising a plurality of words, and describing a product in a group of products, the coreference information indicating coreferences in single web sessions of pairs of products in the group of products, the coreference information further indicating a number of a plurality of words across the group of products, a number of occurrences of each word for both coreferenced products of each pair of products, and a number of occurrences of each word for only one coreferenced product of each pair of products; calculating, on a computer, a score for each word of the plurality of words occurring in the plurality of word groups using the coreference information; selecting, on a computer, a subset of the plurality of words based at least in part on the score; performing, on a computer, a dimensionality reduction on the subset; and serving a web page from the web server, the web page including a description of a first product and a recommendation for a second product, the recommendation being based on a result from the performing step. 4. The method of claim 1 , wherein the coreference record is maintained as a plurality of disjoint spanning trees.
| 0.669011 |
2. The apparatus of claim 1 , wherein the database provides a Representational State Transfer (REST) interface by which the actual values are obtained, and wherein the references to the at least some of the interconnected components and their attributes are embodied as structured uniform resource identifiers (URIs) defined in the REST interface for the at least some of the interconnected components and their attributes, the URIs being used in request messages of the REST interface, and the actual values being returned in corresponding response messages of the REST interface.
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2. The apparatus of claim 1 , wherein the database provides a Representational State Transfer (REST) interface by which the actual values are obtained, and wherein the references to the at least some of the interconnected components and their attributes are embodied as structured uniform resource identifiers (URIs) defined in the REST interface for the at least some of the interconnected components and their attributes, the URIs being used in request messages of the REST interface, and the actual values being returned in corresponding response messages of the REST interface. 3. The apparatus of claim 2 , wherein each response message of the corresponding response messages includes a set of markup-language statements for a component of the at least some of the interconnected components, in which an actual value of an attribute of the component is returned as a tagged value, and including one or more statements having respective URIs for other components of the interconnected components.
| 0.824213 |
17. The method of claim 16 wherein said CLIs are identified as nodes in a directed graph.
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17. The method of claim 16 wherein said CLIs are identified as nodes in a directed graph. 18. The method of claim 17 wherein said matrix is an edge weight matrix and wherein said defined relationships are assigned weights.
| 0.968618 |
19. The ASIC of claim 18 wherein the language model engine stores one or more lookup tables in internal memory to assist in computations required for the CRC function for each of the hash functions of the plurality of hash tables.
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19. The ASIC of claim 18 wherein the language model engine stores one or more lookup tables in internal memory to assist in computations required for the CRC function for each of the hash functions of the plurality of hash tables. 20. The ASIC of claim 19 wherein the one or more lookup tables for each of the hash functions of the plurality of hash tables are adaptable in order to accommodate at least one of a group consisting of: different languages, different language models having different vocabulary sizes, and hash tables of different sizes for a particular language model.
| 0.8921 |
8. A system comprising: a memory comprising instructions executable by one or more processors; and the one or more processors coupled to the memory and operable to execute the instructions, the one or more processors being operable when executing the instructions to: receive a query associated with a first user of a social-networking system, the query comprising a first user attribute, the social-networking system comprising a graph that comprises a plurality of nodes and edges connecting the nodes, at least one node in the graph corresponding to the first user; identify a plurality of second users of a third-party-application system that is external to the social-networking system, each of the second users of the third-party-application system being associated with a user attribute matching the first user attribute of the query; identify one or more third users of the social-networking system, for each of the third users at least one node in the graph corresponding to the third user, at least one of the nodes corresponding to the first user and at least one of the nodes corresponding to a third user being connected to each other by an edge; compare each of the second users of the third-party-application system with each of the third users of the social-networking system to identify one or more of the second users who match the third users based on the first user attribute of the query; and provide a search results page responsive to the receive query, the search results page comprising information associated with each of the second users of the third-party-application system who match the third users.
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8. A system comprising: a memory comprising instructions executable by one or more processors; and the one or more processors coupled to the memory and operable to execute the instructions, the one or more processors being operable when executing the instructions to: receive a query associated with a first user of a social-networking system, the query comprising a first user attribute, the social-networking system comprising a graph that comprises a plurality of nodes and edges connecting the nodes, at least one node in the graph corresponding to the first user; identify a plurality of second users of a third-party-application system that is external to the social-networking system, each of the second users of the third-party-application system being associated with a user attribute matching the first user attribute of the query; identify one or more third users of the social-networking system, for each of the third users at least one node in the graph corresponding to the third user, at least one of the nodes corresponding to the first user and at least one of the nodes corresponding to a third user being connected to each other by an edge; compare each of the second users of the third-party-application system with each of the third users of the social-networking system to identify one or more of the second users who match the third users based on the first user attribute of the query; and provide a search results page responsive to the receive query, the search results page comprising information associated with each of the second users of the third-party-application system who match the third users. 13. The system of claim 8 , wherein: the query further comprises specifies a second user attribute; and the second users are further associated with the second user attribute.
| 0.5 |
18. The method of claim 1 , wherein cells in a second subset of the plurality of cells are associated with a plurality of content names, and wherein the method further comprises: (B) identifying, based on contents of the plurality of cells and the plurality of content names, a formula having at least one term including at least one of the plurality of content names; and (C) associating the formula with at least one of the plurality of cells.
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18. The method of claim 1 , wherein cells in a second subset of the plurality of cells are associated with a plurality of content names, and wherein the method further comprises: (B) identifying, based on contents of the plurality of cells and the plurality of content names, a formula having at least one term including at least one of the plurality of content names; and (C) associating the formula with at least one of the plurality of cells. 19. The method of claim 18 , wherein (B) comprises identifying a formula having a plurality of terms, wherein each of the plurality of terms includes at least one of the plurality of content names.
| 0.853764 |
8. The method of claim 4 , wherein the forming the list is a result of performing clustering of the plurality of network nodes, the clustering being based on the single feature vector for each of the plurality of network nodes.
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8. The method of claim 4 , wherein the forming the list is a result of performing clustering of the plurality of network nodes, the clustering being based on the single feature vector for each of the plurality of network nodes. 10. The method of claim 8 , wherein the clustering is performed using a nested method in which one or more of said plurality of network nodes are initially clustered based on a sub-set of attributes and then re-clustered by iteratively considering additional attributes.
| 0.916922 |
27. The computer-implemented method of claim 25 , wherein computing and determining further comprises: reducing the Levenshtein distance value between a group of words and the text, on detecting the Levenshtein distance value between the group of words and the text is within a first threshold wherein reducing the Levenshtein distance between a group of words and the text is based on a correlation of characters contributing to the Levenshtein distance value with one or more characters commonly misinterpreted by an optical character recognition, OCR, process; and wherein determining further comprises identifying the group of words as an instance of the group of text when the reduced Levenshtein distance value is within a second threshold.
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27. The computer-implemented method of claim 25 , wherein computing and determining further comprises: reducing the Levenshtein distance value between a group of words and the text, on detecting the Levenshtein distance value between the group of words and the text is within a first threshold wherein reducing the Levenshtein distance between a group of words and the text is based on a correlation of characters contributing to the Levenshtein distance value with one or more characters commonly misinterpreted by an optical character recognition, OCR, process; and wherein determining further comprises identifying the group of words as an instance of the group of text when the reduced Levenshtein distance value is within a second threshold. 28. The computer-implemented method of claim 27 , wherein the first and second thresholds are based on a number of characters contained within the text.
| 0.812708 |
18. The character processor device of claim 13 wherein operating a primary state machine to control invocation of the respective construct state machines comprises: detecting a sequence of characters representative of a processing instruction element and invoking a processing instruction element state machine; and operating the processing instruction element state machine to produce at least one processing instruction data element encoded item containing type, length, value representations for at least one of: a processing instruction data element; a partial processing instruction data element.
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18. The character processor device of claim 13 wherein operating a primary state machine to control invocation of the respective construct state machines comprises: detecting a sequence of characters representative of a processing instruction element and invoking a processing instruction element state machine; and operating the processing instruction element state machine to produce at least one processing instruction data element encoded item containing type, length, value representations for at least one of: a processing instruction data element; a partial processing instruction data element. 19. The character processor device of claim 18 wherein the processing instruction is a non-declaration processing instruction and wherein operating the processing instruction element state machine to produce at least one processing instruction data element encoded item comprises: producing a non-declaration processing instruction target data element; and producing a non-declaration processing instruction value data element.
| 0.909551 |
31. A computer implemented method for processing database content, the method comprising the steps of: receiving one or more data objects associated with a database at one or more remote computers; parsing one or more source documents to identify at least one term based on one or more predetermined rules; identifying content for the at least one term; linking the content with the at least one term; and automatically associating the at least one term in the one or more source documents with at least one link; wherein the at least one link denotes an association between the at least one term and the linked content; wherein the one or more data objects associated with the database provide a representation of at least a portion of the database at the one or more remote computers; and wherein the linked content is displayed on a user interface based upon a user interaction with at least a portion of the one or more source documents.
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31. A computer implemented method for processing database content, the method comprising the steps of: receiving one or more data objects associated with a database at one or more remote computers; parsing one or more source documents to identify at least one term based on one or more predetermined rules; identifying content for the at least one term; linking the content with the at least one term; and automatically associating the at least one term in the one or more source documents with at least one link; wherein the at least one link denotes an association between the at least one term and the linked content; wherein the one or more data objects associated with the database provide a representation of at least a portion of the database at the one or more remote computers; and wherein the linked content is displayed on a user interface based upon a user interaction with at least a portion of the one or more source documents. 37. The method of claim 31 , wherein the at least one term is visibly enhanced to notify the user of available content.
| 0.511352 |
18. A tangible computer-readable storage medium storing instructions for controlling a computing device for generating a database for a text-to-speech (TTS) voice, the instructions comprising: matching via a processor every spoken word associated with a TTS voice database with a smallest set of possible pronunciations for each word, the smallest set being generated by: automatically determining a dialect and linguistic context using linguistic rules; empirically determining idiosyncratic speaker characteristics; and determining a subject domain; and dynamically generating a pronunciation dictionary on a word-by-word basis using the smallest set.
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18. A tangible computer-readable storage medium storing instructions for controlling a computing device for generating a database for a text-to-speech (TTS) voice, the instructions comprising: matching via a processor every spoken word associated with a TTS voice database with a smallest set of possible pronunciations for each word, the smallest set being generated by: automatically determining a dialect and linguistic context using linguistic rules; empirically determining idiosyncratic speaker characteristics; and determining a subject domain; and dynamically generating a pronunciation dictionary on a word-by-word basis using the smallest set. 19. The computer-readable medium of claim 18 , wherein the dynamically generated pronunciation dictionary accounts for reading errors and idiosyncrasies of speakers.
| 0.573454 |
2. The method of claim 1 , wherein the call comprises a domain-specific language function call made using a core application programming interface.
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2. The method of claim 1 , wherein the call comprises a domain-specific language function call made using a core application programming interface. 3. The method of claim 2 , wherein the second scripting language comprises a domain-specific language and the first scripting language comprises one or more of a Python, Jython, and a JRuby based language.
| 0.943094 |
11. The apparatus of claim 9 , wherein the pre-processor is further configured to: phonetically transcribe speech documents in the set of training documents into an intermediate representative language, thereby creating phonetic transcriptions; convert the set of training documents from native format to UTF-8 format; and segment each document in the set of training documents.
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11. The apparatus of claim 9 , wherein the pre-processor is further configured to: phonetically transcribe speech documents in the set of training documents into an intermediate representative language, thereby creating phonetic transcriptions; convert the set of training documents from native format to UTF-8 format; and segment each document in the set of training documents. 12. The apparatus of claim 11 , wherein the pre-processor configured to segment each document comprises the pre-processor configured to tokenize the phonetic transcriptions and the converted documents to create counts for index terms and phonemes.
| 0.86292 |
1. A clinical decision support system including: a processor: a computer-readable medium encoded with a crawler agent component, wherein the crawler agent component receives a search parameter, wherein the search parameter specifies a criteria for evidence data to be searched for, wherein the search parameter includes a context limiter, and wherein the crawler agent component initiates a simultaneous search of a plurality of evidence sources based at least in part on the search parameter, wherein the search identifies the evidence data, wherein the evidence data is utilized by the clinical decision support system to provide decision support to a healthcare provider for a patient, wherein at least one of the plurality of evidence sources is selected based at least in part on the context limiter, the context limiter restricting evidence to be searched for to an area in which at least one healthcare facility is located and/or healthcare facility capabilities; wherein the crawler agent component provides a link to the source of the evidence data, wherein each of the plurality of evidence sources comprises one or more of PACS, RIS, and/or CVIS, wherein the search parameter comprises one or more of patient name, patient identifier, order number and/or exam type, and wherein the evidence data comprises one or more of prior exams, images, key image notes, laboratory exams and reports, allergies, pathology results, medication, alerts, and/or document images, and a recommendation component that generates a recommendation for a diagnosis and/or course of treatment for a patient based at least in part on the evidence data.
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1. A clinical decision support system including: a processor: a computer-readable medium encoded with a crawler agent component, wherein the crawler agent component receives a search parameter, wherein the search parameter specifies a criteria for evidence data to be searched for, wherein the search parameter includes a context limiter, and wherein the crawler agent component initiates a simultaneous search of a plurality of evidence sources based at least in part on the search parameter, wherein the search identifies the evidence data, wherein the evidence data is utilized by the clinical decision support system to provide decision support to a healthcare provider for a patient, wherein at least one of the plurality of evidence sources is selected based at least in part on the context limiter, the context limiter restricting evidence to be searched for to an area in which at least one healthcare facility is located and/or healthcare facility capabilities; wherein the crawler agent component provides a link to the source of the evidence data, wherein each of the plurality of evidence sources comprises one or more of PACS, RIS, and/or CVIS, wherein the search parameter comprises one or more of patient name, patient identifier, order number and/or exam type, and wherein the evidence data comprises one or more of prior exams, images, key image notes, laboratory exams and reports, allergies, pathology results, medication, alerts, and/or document images, and a recommendation component that generates a recommendation for a diagnosis and/or course of treatment for a patient based at least in part on the evidence data. 7. The system of claim 1 , wherein the crawler agent component is located at a first healthcare facility and wherein at least one of the plurality of evidence sources is located at a second healthcare facility, wherein the second healthcare facility is geographically remote from the first healthcare facility.
| 0.5 |
8. The text data processing method according to claim 7 , wherein the record of symbol insertion is set, by the processor, in accordance with an insertion frequency of the symbol in the block obtained by dividing text from a same speaker.
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8. The text data processing method according to claim 7 , wherein the record of symbol insertion is set, by the processor, in accordance with an insertion frequency of the symbol in the block obtained by dividing text from a same speaker. 9. The text data processing method according to claim 8 , wherein the processor calculates number of symbol insertions in the block, and determines that the symbol edit is necessary until number of symbols in the block reaches the number of symbol insertions.
| 0.876896 |
9. A computer program product for determining compliance of content with a content policy, the computer program product comprising a non-transitory computer-readable storage medium containing computer program code for: receiving a content item comprising text and one or more images; extracting a plurality of text signals from the text; extracting a plurality of image signals from the one or more images; inputting the plurality of text signals and the plurality of image signals into a two-tier classifier system by inputting the plurality of text signals into a text classifier model of a first tier of the two-tier classifier system, inputting the plurality of image signals into an image classifier model of the first tier of the two tier-classifier system, and inputting output classifications of the text classifier model and of the image classifier model into a second-tier classifier model, the second-tier classifier outputting a confidence value expressing likelihood of compliance with a content policy of an online system; comparing the confidence value against a pre-defined threshold value; and based on the comparison, assigning a compliance classification to the content item.
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9. A computer program product for determining compliance of content with a content policy, the computer program product comprising a non-transitory computer-readable storage medium containing computer program code for: receiving a content item comprising text and one or more images; extracting a plurality of text signals from the text; extracting a plurality of image signals from the one or more images; inputting the plurality of text signals and the plurality of image signals into a two-tier classifier system by inputting the plurality of text signals into a text classifier model of a first tier of the two-tier classifier system, inputting the plurality of image signals into an image classifier model of the first tier of the two tier-classifier system, and inputting output classifications of the text classifier model and of the image classifier model into a second-tier classifier model, the second-tier classifier outputting a confidence value expressing likelihood of compliance with a content policy of an online system; comparing the confidence value against a pre-defined threshold value; and based on the comparison, assigning a compliance classification to the content item. 13. The computer program product of claim 9 , wherein the plurality of image signals comprises an indication that the one or more images contains a face.
| 0.7311 |
1. A computer implemented method, comprising: receiving search request data specifying a search request, the search request comprising a drawing represented by a set of line strokes, wherein each line stroke represents a trace of a moving input point; identifying line segments from the line strokes in the set; comparing the identified line segments to reference line segments, wherein each of the reference line segments represents a portion of a corresponding reference drawing; identifying, by one or more data processors, a candidate reference drawing based on the comparison of the identified line segments with reference line segments representing the candidate reference drawing; identifying a keyword for the candidate reference drawing, wherein the keyword is a term determined to be relevant to a subject matter of the candidate reference drawing; in response to receiving the search request data, providing search results data specifying search results responsive to the keyword; identifying multiple keywords for the candidate reference drawing; providing the multiple keywords for the candidate reference drawing for selection on a search results page; receiving user selection of a particular one of the multiple keywords that are provided for selection on the search results page; and performing a search using the particular one of the multiple keywords in a search query in response to user selection of the particular one of the multiple keywords.
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1. A computer implemented method, comprising: receiving search request data specifying a search request, the search request comprising a drawing represented by a set of line strokes, wherein each line stroke represents a trace of a moving input point; identifying line segments from the line strokes in the set; comparing the identified line segments to reference line segments, wherein each of the reference line segments represents a portion of a corresponding reference drawing; identifying, by one or more data processors, a candidate reference drawing based on the comparison of the identified line segments with reference line segments representing the candidate reference drawing; identifying a keyword for the candidate reference drawing, wherein the keyword is a term determined to be relevant to a subject matter of the candidate reference drawing; in response to receiving the search request data, providing search results data specifying search results responsive to the keyword; identifying multiple keywords for the candidate reference drawing; providing the multiple keywords for the candidate reference drawing for selection on a search results page; receiving user selection of a particular one of the multiple keywords that are provided for selection on the search results page; and performing a search using the particular one of the multiple keywords in a search query in response to user selection of the particular one of the multiple keywords. 10. The computer-implemented method of claim 1 , wherein the search results that are responsive to the keyword include textual search results that identify a title of a web page and a portion of text extracted from the web page.
| 0.618649 |
15. A method of segmenting information to a first user in generating a first user personal characteristic profile, the method comprising: displaying at least one pre-generated compounded topic to said first user, said at least one pre-generated compounded topic generated from a correlated content; said first user selecting a pre-generated compounded topic; receiving a selection of said at least one question by said first user, said at least question including a plurality of response forms; receiving a selection of a response form by said first user; and displaying said correlated content to said first user, wherein the correlated content is associated with a second user personal characteristic profile.
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15. A method of segmenting information to a first user in generating a first user personal characteristic profile, the method comprising: displaying at least one pre-generated compounded topic to said first user, said at least one pre-generated compounded topic generated from a correlated content; said first user selecting a pre-generated compounded topic; receiving a selection of said at least one question by said first user, said at least question including a plurality of response forms; receiving a selection of a response form by said first user; and displaying said correlated content to said first user, wherein the correlated content is associated with a second user personal characteristic profile. 17. The method of claim 15 , including displaying a correlated content, opposite to said correlated content to said response form.
| 0.656364 |
15. The computer system according to claim 14 , wherein the at least one computer is further programmed to: adapt the site specific language model to create a task language model; and output the task language model.
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15. The computer system according to claim 14 , wherein the at least one computer is further programmed to: adapt the site specific language model to create a task language model; and output the task language model. 16. The computer system according to claim 15 , wherein adapting the site-specific language model further comprises: updating a set of statistics for the selected language model.
| 0.81083 |
1. A system for analyzing access control configurations, comprising: a processor and memory; an operating system having resources and identifications of principals, the principals having access control privileges relating to the resources, the access control privileges described by access control metadata; an access control scanner component that receives the access control metadata, uses the metadata to determine relationships between the principals and the resources, and emits access control relations information, wherein the access control scanner component includes a mechanism layer that is configured to be specific to an operating system, and emits one or more sets of permissions in relation to resources, and a policy layer that is configured be general across multiple operating systems, the policy layer receives the one or more sets of permissions and generates one or more derivation trees that each indicate a possible vulnerability based on the relationships between the principals and the resources; and an access control inference engine that receives the emitted access control relations information and an access control policy model defining desired security policies, analyzes the received information and model, and emits a vulnerability report.
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1. A system for analyzing access control configurations, comprising: a processor and memory; an operating system having resources and identifications of principals, the principals having access control privileges relating to the resources, the access control privileges described by access control metadata; an access control scanner component that receives the access control metadata, uses the metadata to determine relationships between the principals and the resources, and emits access control relations information, wherein the access control scanner component includes a mechanism layer that is configured to be specific to an operating system, and emits one or more sets of permissions in relation to resources, and a policy layer that is configured be general across multiple operating systems, the policy layer receives the one or more sets of permissions and generates one or more derivation trees that each indicate a possible vulnerability based on the relationships between the principals and the resources; and an access control inference engine that receives the emitted access control relations information and an access control policy model defining desired security policies, analyzes the received information and model, and emits a vulnerability report. 11. The system of claim 1 wherein the access control scanner component can be substituted with a different access control scanner component for use with a different operating system.
| 0.515614 |
18. The content reproduction device according to claim 17 , wherein the one or more memory devices stores instructions that further cause the one or more processing devices to: generate the historical data so that the historical data includes, in association with each other, (i) position information indicative of a position of the reproduction of the content at which position the input step accepted the input operation for starting the search and (ii) the access information for the access to the result of the search by the search step; and with reference to the historical data generated by the historical data generating step, specify timing of displaying the object, the content reproduction device further comprising, wherein the one or more memory devices stores instructions that further cause the one or more processing devices to: in a case where the object displayed by the object display step has been selected, display the search result obtained with use of the access information included in the historical data.
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18. The content reproduction device according to claim 17 , wherein the one or more memory devices stores instructions that further cause the one or more processing devices to: generate the historical data so that the historical data includes, in association with each other, (i) position information indicative of a position of the reproduction of the content at which position the input step accepted the input operation for starting the search and (ii) the access information for the access to the result of the search by the search step; and with reference to the historical data generated by the historical data generating step, specify timing of displaying the object, the content reproduction device further comprising, wherein the one or more memory devices stores instructions that further cause the one or more processing devices to: in a case where the object displayed by the object display step has been selected, display the search result obtained with use of the access information included in the historical data. 19. The content reproduction device according to claim 18 , wherein the one or more memory devices stores instructions that further cause the one or more processing devices to: search the database by a keyword of which the input step has accepted input; generate the historical data so that the historical data includes the keyword of which the input step has accepted the input; and display the object including the keyword included in the historical data generated by the historical data generating step.
| 0.637647 |
1. A computer-implemented method for extracting meaning from a plurality of documents, the method comprising: identifying, by a computer, a meaning taxonomy including a plurality of selected concepts; identifying a group of syntactic structures including at least one syntactic structure; associating at least one of the group of syntactic structures with at least one selected concept of the plurality of selected concepts; applying at least one expert rule selected from a group of expert rules to at least one document of the plurality of documents, the group of expert rules being associated with the at least one selected concept, the at least one expert rule including a plurality of logical propositions, at least one logical proposition of the plurality of logical propositions including an evaluation of whether an association exists between one or more of the group of syntactic structures associated with the at least one selected concept and one or more syntactic structures included in the at least one document of the plurality of documents; and associating, responsive to existence of the association, the at least one document of the plurality of documents with the at least one selected concept of the plurality of selected concepts.
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1. A computer-implemented method for extracting meaning from a plurality of documents, the method comprising: identifying, by a computer, a meaning taxonomy including a plurality of selected concepts; identifying a group of syntactic structures including at least one syntactic structure; associating at least one of the group of syntactic structures with at least one selected concept of the plurality of selected concepts; applying at least one expert rule selected from a group of expert rules to at least one document of the plurality of documents, the group of expert rules being associated with the at least one selected concept, the at least one expert rule including a plurality of logical propositions, at least one logical proposition of the plurality of logical propositions including an evaluation of whether an association exists between one or more of the group of syntactic structures associated with the at least one selected concept and one or more syntactic structures included in the at least one document of the plurality of documents; and associating, responsive to existence of the association, the at least one document of the plurality of documents with the at least one selected concept of the plurality of selected concepts. 6. The method according to claim 1 , wherein associating the at least one of the group of syntactic structures comprises associating a plurality of the group of syntactic structures with the at least one selected concept of the plurality of selected concepts.
| 0.789244 |
1. A method comprising: receiving, from a client system of a first user of an online social network, a structured query comprising references to one or more selected objects associated with the online social network; generating a query command based on the structured query, wherein the query command comprises an inner query constraint and an outer query constraint; identifying a first set of objects matching the inner query constraint and at least in part matching the outer query constraint; identifying a second set of objects matching the outer query constraint; and generating one or more search results based on the first and second sets of objects, wherein each search result corresponds to an object of the plurality of objects.
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1. A method comprising: receiving, from a client system of a first user of an online social network, a structured query comprising references to one or more selected objects associated with the online social network; generating a query command based on the structured query, wherein the query command comprises an inner query constraint and an outer query constraint; identifying a first set of objects matching the inner query constraint and at least in part matching the outer query constraint; identifying a second set of objects matching the outer query constraint; and generating one or more search results based on the first and second sets of objects, wherein each search result corresponds to an object of the plurality of objects. 18. The method of claim 1 , wherein the inner query constraint is nested in the outer query constraint.
| 0.660898 |
37. At least one non-transitory computer-readable storage medium encoded with executable instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising: determining, by a biometric enrollment system and for each person in a group of multiple, different people, a similarity score that represents a similarity between a biometric image of at least a portion of the corresponding person from the group of multiple, different people and a reference image, wherein the reference image is used in determining all of the similarity scores for the group of multiple, different people; sorting biometric data that includes all of the determined similarity scores using the determined similarity scores; maintaining, in electronic storage and for the group of multiple, different people, the biometric data that includes all of the sorted similarity scores; accessing a particular biometric image of at least a portion of a particular person; accessing the reference image used in computing all of the similarity scores maintained in the electronic storage; computing a particular similarity score that represents similarity between the accessed particular biometric image and the reference image; searching, by a biometric authentication system that includes at least one processor and using the computed particular similarity score, the sorted similarity scores included in the biometric data for the group of multiple, different people; and outputting a result based on determination of whether the electronic storage includes data for the particular person in the biometric data.
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37. At least one non-transitory computer-readable storage medium encoded with executable instructions that, when executed by at least one processor, cause the at least one processor to perform operations comprising: determining, by a biometric enrollment system and for each person in a group of multiple, different people, a similarity score that represents a similarity between a biometric image of at least a portion of the corresponding person from the group of multiple, different people and a reference image, wherein the reference image is used in determining all of the similarity scores for the group of multiple, different people; sorting biometric data that includes all of the determined similarity scores using the determined similarity scores; maintaining, in electronic storage and for the group of multiple, different people, the biometric data that includes all of the sorted similarity scores; accessing a particular biometric image of at least a portion of a particular person; accessing the reference image used in computing all of the similarity scores maintained in the electronic storage; computing a particular similarity score that represents similarity between the accessed particular biometric image and the reference image; searching, by a biometric authentication system that includes at least one processor and using the computed particular similarity score, the sorted similarity scores included in the biometric data for the group of multiple, different people; and outputting a result based on determination of whether the electronic storage includes data for the particular person in the biometric data. 40. The computer-readable storage medium of claim 37 : wherein accessing the particular biometric image of at least the portion of the particular person comprises accessing an image of a face of the particular person; wherein accessing the reference image comprises accessing a reference image of a face of a reference person; and wherein computing the particular similarity score that represents similarity between the accessed particular biometric image and the reference image comprises computing a similarity score that represents similarity between the accessed image of the face of the particular person and the reference image of the face of the reference person.
| 0.645796 |
37. An article comprising a machine-readable medium storing instructions operable to cause a physical-document monitoring device comprising one or more machines to perform operations comprising: determining whether a state of a document has been sensed with a sensor coupled to a document coupling device; determining the document state with a computer coupled to the sensor and the document coupling device; and generating a wireless message to send a representation of the document state to a remote device.
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37. An article comprising a machine-readable medium storing instructions operable to cause a physical-document monitoring device comprising one or more machines to perform operations comprising: determining whether a state of a document has been sensed with a sensor coupled to a document coupling device; determining the document state with a computer coupled to the sensor and the document coupling device; and generating a wireless message to send a representation of the document state to a remote device. 42. The article of claim 37 , wherein the instructions are further operable to cause one or more machines to perform operations comprising determining whether document meta-data has been received.
| 0.549275 |
8. A computer program product comprising a non-transitory computer readable medium having a set of instructions stored thereon, the instructions, which when executed by a computer system, perform: storing metadata values for each of a plurality of content objects in corresponding metadata value storage locations in a data storage unit containing an index, the plurality of content objects stored in a repository accessible by the computer system, the index having multiple metadata indices for metadata fields, each metadata field of the metadata fields having a unique identity and a corresponding metadata value storage location in the data storage unit, wherein the index in the data storage unit further comprises multiple aggregate metadata indices in addition to the multiple metadata indices, wherein each aggregate metadata index of the multiple aggregate metadata indices includes a dictionary and a single defined metadata field, the single defined metadata field associated with a designated set of metadata fields including at least two of the metadata fields from the multiple metadata indices, each of the at least two of the metadata fields retaining the unique identity and the corresponding metadata value storage location in the data storage unit, the at least two of the metadata fields being logically related or associated to one another, wherein the dictionary contains and identifies terms contained in particular metadata values associated with the at least two of the metadata fields from the multiple metadata indices, the aggregate metadata index further containing, for each term, one or more pointers identifying content objects which have metadata fields containing the particular metadata values; receiving a search query containing a specific search term over a network via a search interface operating on a client computer having the defined metadata field of the aggregate metadata index; searching the dictionary of the aggregate metadata index for a term that matches the specific search term, the term pointing, via associated one or more pointers, to one or more content objects which have one or more metadata values that contain the specific search term; retrieving, from corresponding metadata value storage locations, the one or more metadata values associated with the one or more content objects and containing the specific search term; and returning to the client computer over the network via the search interface at least a metadata value of the one or more metadata values associated with the one or more content objects.
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8. A computer program product comprising a non-transitory computer readable medium having a set of instructions stored thereon, the instructions, which when executed by a computer system, perform: storing metadata values for each of a plurality of content objects in corresponding metadata value storage locations in a data storage unit containing an index, the plurality of content objects stored in a repository accessible by the computer system, the index having multiple metadata indices for metadata fields, each metadata field of the metadata fields having a unique identity and a corresponding metadata value storage location in the data storage unit, wherein the index in the data storage unit further comprises multiple aggregate metadata indices in addition to the multiple metadata indices, wherein each aggregate metadata index of the multiple aggregate metadata indices includes a dictionary and a single defined metadata field, the single defined metadata field associated with a designated set of metadata fields including at least two of the metadata fields from the multiple metadata indices, each of the at least two of the metadata fields retaining the unique identity and the corresponding metadata value storage location in the data storage unit, the at least two of the metadata fields being logically related or associated to one another, wherein the dictionary contains and identifies terms contained in particular metadata values associated with the at least two of the metadata fields from the multiple metadata indices, the aggregate metadata index further containing, for each term, one or more pointers identifying content objects which have metadata fields containing the particular metadata values; receiving a search query containing a specific search term over a network via a search interface operating on a client computer having the defined metadata field of the aggregate metadata index; searching the dictionary of the aggregate metadata index for a term that matches the specific search term, the term pointing, via associated one or more pointers, to one or more content objects which have one or more metadata values that contain the specific search term; retrieving, from corresponding metadata value storage locations, the one or more metadata values associated with the one or more content objects and containing the specific search term; and returning to the client computer over the network via the search interface at least a metadata value of the one or more metadata values associated with the one or more content objects. 12. The computer program product of claim 8 , wherein the instructions, which when executed by the computer system, further perform generating an aggregate metadata index.
| 0.555667 |
1. A computing device, comprising: at least one processor circuit; and a memory that stores program code configured to be executed by the at least one processor circuit to perform operations, the operations including: querying a plurality of textual messages of a message repository with a plurality of sets of key phrases to determine and score textual messages that include one or more of the key phrases of the sets, each scored textual message including a suspect, a potential victim, and a score, each suspect-to-potential victim pair corresponding to a conversation that includes the scored textual messages between the suspect and potential victim of the pair; and determining a plurality of conversation risk scores based at least on the scored textual messages, each conversation risk score indicating an estimate of a risk of predatory behavior occurring during the corresponding conversation.
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1. A computing device, comprising: at least one processor circuit; and a memory that stores program code configured to be executed by the at least one processor circuit to perform operations, the operations including: querying a plurality of textual messages of a message repository with a plurality of sets of key phrases to determine and score textual messages that include one or more of the key phrases of the sets, each scored textual message including a suspect, a potential victim, and a score, each suspect-to-potential victim pair corresponding to a conversation that includes the scored textual messages between the suspect and potential victim of the pair; and determining a plurality of conversation risk scores based at least on the scored textual messages, each conversation risk score indicating an estimate of a risk of predatory behavior occurring during the corresponding conversation. 2. The computing device of claim 1 , wherein said determining a plurality of conversation risk scores based at least on the scored textual messages comprises: generating a conversation risk score for each suspect-to-potential victim pair by analyzing textual messages of the corresponding conversation, including: selecting a highest score for the scored textual messages of the corresponding conversation for each set of the plurality of sets of key phrases having a score to generate one or more highest scores, discarding the suspect-to-potential victim pair if the one or more highest scores includes fewer than a predetermined number of highest scores, combining the one or more highest scores to generate an average suspect key phrases score, multiplying the average suspect key phrases score by a group count ID to generate a suspect textual score, generating an estimated age imbalance score, and modifying the suspect textual score according to the estimated age imbalance score to generate a conversation risk score for the suspect-to-potential victim pair.
| 0.696231 |
11. A non-transitory computer readable medium having stored thereon machine readable instructions for matching regular expressions including boundary symbols, the machine readable instructions when executed cause a computer system to: receive an input string; receive a regular expression including a boundary symbol; and transform, by a processor, the regular expression into an automaton such that a set of strings accepted by the automaton is the same as a set of strings described by the regular expression, wherein the automaton is a final automaton derived from a plurality of intermediate automata, and wherein transforming the regular expression into the final automaton further includes transforming the regular expression into a first intermediate automaton that accepts a string over an extended alphabet including boundary symbols.
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11. A non-transitory computer readable medium having stored thereon machine readable instructions for matching regular expressions including boundary symbols, the machine readable instructions when executed cause a computer system to: receive an input string; receive a regular expression including a boundary symbol; and transform, by a processor, the regular expression into an automaton such that a set of strings accepted by the automaton is the same as a set of strings described by the regular expression, wherein the automaton is a final automaton derived from a plurality of intermediate automata, and wherein transforming the regular expression into the final automaton further includes transforming the regular expression into a first intermediate automaton that accepts a string over an extended alphabet including boundary symbols. 12. The non-transitory computer readable medium of claim 11 , further comprising machine readable instructions to: process the input string by the automaton to determine if the input string matches the regular expression.
| 0.744177 |
3. The method of claim 1 , using the one or more features extracted from the given URL and the usefulness prediction model to generate the usefulness prediction in connection with the given URL further comprising: generating a positive usefulness prediction value in connection with the given URL using the one or more features extracted from the given URL and the usefulness prediction model; generating a negative usefulness prediction value in connection with the given URL using the one or more features extracted from the given URL and the usefulness prediction model; and comparing the positive usefulness prediction value with the negative usefulness prediction value to generate the usefulness prediction in connection with the given URL.
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3. The method of claim 1 , using the one or more features extracted from the given URL and the usefulness prediction model to generate the usefulness prediction in connection with the given URL further comprising: generating a positive usefulness prediction value in connection with the given URL using the one or more features extracted from the given URL and the usefulness prediction model; generating a negative usefulness prediction value in connection with the given URL using the one or more features extracted from the given URL and the usefulness prediction model; and comparing the positive usefulness prediction value with the negative usefulness prediction value to generate the usefulness prediction in connection with the given URL. 10. The method of claim 3 , the generating a negative usefulness prediction value further comprising: determining the negative usefulness prediction value using a product, P, of a feature vector that identifies the features extracted from the given URL and a weighting vector that includes a weighting for each of the features extracted from the given URL to generate the negative usefulness prediction value using a formula:
1−[1/(1+e −P )].
| 0.799894 |
11. A system for presenting results of a search customized using content preferences learned about a user, the system comprising: a non-transitory computer memory store comprising instructions in computer readable form that when executed cause a computer system to receive a user input action for interacting with an application on a user device; in response to receiving the user input action, send query information to a search engine, the query information including user information, the user information including (i) context information describing an environment in which the user input action was received, the context information adapted into a syntax understandable by the search engine, and (ii) a user signature representing content preferences learned about the user; generate customized search results by receiving a set of search results and auxiliary information from the search engine in response to sending the query information, the auxiliary information including information describing attributes of each search result of the set of search results that led to each search result being chosen by the search engine; order the set of search results based at least in part on the auxiliary information; and present, to the user, the ordered set of search results customized using the content preferences learned about the user.
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11. A system for presenting results of a search customized using content preferences learned about a user, the system comprising: a non-transitory computer memory store comprising instructions in computer readable form that when executed cause a computer system to receive a user input action for interacting with an application on a user device; in response to receiving the user input action, send query information to a search engine, the query information including user information, the user information including (i) context information describing an environment in which the user input action was received, the context information adapted into a syntax understandable by the search engine, and (ii) a user signature representing content preferences learned about the user; generate customized search results by receiving a set of search results and auxiliary information from the search engine in response to sending the query information, the auxiliary information including information describing attributes of each search result of the set of search results that led to each search result being chosen by the search engine; order the set of search results based at least in part on the auxiliary information; and present, to the user, the ordered set of search results customized using the content preferences learned about the user. 16. The system of claim 11 , the computer memory store further comprising instructions that cause the computer system to select the search engine to which the query information is sent based on a measure of a use by the user of the search engine.
| 0.760883 |
8. A method for remotely arming a failsafe mode for a first device using a device control profile, comprising: receiving, at the first device, an arm failsafe request configured to cause the first device to arm a configuration failsafe, wherein the configuration failsafe is configured to prevent partial configuration or improper configuration of the first device; determining, at the first device, whether the configuration failsafe has already been armed; and transmitting, to a remote device that sent the arm failsafe request, a status report indicating whether the requested configuration failsafe is able to be armed.
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8. A method for remotely arming a failsafe mode for a first device using a device control profile, comprising: receiving, at the first device, an arm failsafe request configured to cause the first device to arm a configuration failsafe, wherein the configuration failsafe is configured to prevent partial configuration or improper configuration of the first device; determining, at the first device, whether the configuration failsafe has already been armed; and transmitting, to a remote device that sent the arm failsafe request, a status report indicating whether the requested configuration failsafe is able to be armed. 10. The method of claim 8 , wherein the arm failsafe request comprises: a failsafe mode identifier that indicates a type of failsafe mode to be initiated; and a failsafe token configured to indicate to other devices connecting to the first device that the first device has already had its configuration failsafe armed.
| 0.62037 |
6. An information handling system comprising: one or more processors; a memory coupled to at least one of the processors; a display; and a set of instructions stored in the memory and executed by at least one of the processors to mine threaded online discussions, wherein the set of instructions perform actions of: performing, by the information handling system, a natural language processing (NLP) analysis of one or more threaded discussions pertaining to a given topic, wherein the analysis is performed across one or more web sites with each of the web sites including one or more of the threaded discussions, wherein the analysis results in a plurality of harvested discussions; correlating the plurality of harvested discussions across a plurality of threads from the one or more web sites; identifying a question from the harvested discussions; identifying a plurality of candidate answers from the harvested discussions, wherein each of the plurality of candidate answers pertain to the identified question; aggregating and merging a selected plurality of harvested discussions corresponding to each of the candidate answers, wherein the selected plurality of harvested discussions are supporting evidence corresponding to the respective candidate answer; generating a supporting evidence score based on one or more factors of the supporting evidence for each of the candidate answers, wherein at least one of the factors is selected from the group consisting of a quality of the supporting evidence, and a quantity of the supporting evidence; generating an answer post score for each of the candidate answers based on an identification of a rating within the threaded discussions pertaining to the respective candidate answer; generating a post provider score for each of the candidate answers based on an identified expertise level that corresponds to a provider of the respective candidate answer; generating a follow-up score for each of the candidate answers based on one or more follow-up comments from posters that indicate that the respective candidate answer was correct; and scoring each of the plurality of candidate answers, wherein the scoring calculates an overall score corresponding to each of the candidate answers, wherein the overall score is based upon one or more component scores selected from the group consisting of the supporting evidence score, the answer post score, the post provider score, and the follow-up score, and wherein a selected answer has the highest overall score when compared to the other candidate answers.
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6. An information handling system comprising: one or more processors; a memory coupled to at least one of the processors; a display; and a set of instructions stored in the memory and executed by at least one of the processors to mine threaded online discussions, wherein the set of instructions perform actions of: performing, by the information handling system, a natural language processing (NLP) analysis of one or more threaded discussions pertaining to a given topic, wherein the analysis is performed across one or more web sites with each of the web sites including one or more of the threaded discussions, wherein the analysis results in a plurality of harvested discussions; correlating the plurality of harvested discussions across a plurality of threads from the one or more web sites; identifying a question from the harvested discussions; identifying a plurality of candidate answers from the harvested discussions, wherein each of the plurality of candidate answers pertain to the identified question; aggregating and merging a selected plurality of harvested discussions corresponding to each of the candidate answers, wherein the selected plurality of harvested discussions are supporting evidence corresponding to the respective candidate answer; generating a supporting evidence score based on one or more factors of the supporting evidence for each of the candidate answers, wherein at least one of the factors is selected from the group consisting of a quality of the supporting evidence, and a quantity of the supporting evidence; generating an answer post score for each of the candidate answers based on an identification of a rating within the threaded discussions pertaining to the respective candidate answer; generating a post provider score for each of the candidate answers based on an identified expertise level that corresponds to a provider of the respective candidate answer; generating a follow-up score for each of the candidate answers based on one or more follow-up comments from posters that indicate that the respective candidate answer was correct; and scoring each of the plurality of candidate answers, wherein the scoring calculates an overall score corresponding to each of the candidate answers, wherein the overall score is based upon one or more component scores selected from the group consisting of the supporting evidence score, the answer post score, the post provider score, and the follow-up score, and wherein a selected answer has the highest overall score when compared to the other candidate answers. 8. The information handling system of claim 6 wherein the actions further comprise: identifying a plurality of follow-up postings corresponding to the identified question; analyzing each of the follow-up postings to identify a conversational move corresponding to each of the follow up postings, wherein at least one of the conversational postings is selected from the group consisting of an answer, a clarification, a rejection, or a different conversational move; and generating a contribution tree based on the follow-up postings and their identified conversational moves.
| 0.5 |
1. A method for clustering annotators via a distributed data annotation process, comprising: obtaining a set of source data using a distributed data annotation server system, where a piece of source data in the set of source data comprises at least one identifying feature; determining a training data set representative of the set of source data using the distributed data annotation server system, where each piece of source data in the training data set comprises source data metadata describing the ground truth for the piece of source data, where the ground truth for a piece of source data describes the features contained in the piece of source data and a correct label associated with each feature; obtaining sets of annotations from a set of annotators for a portion of the training data set using the distributed data annotation server system, where an annotation identifies one or more features within a piece of source data in the training data set; for each annotator: determining annotator recall metadata based on the set of annotations provided by the annotator for the training data set using the distributed data annotation server system, where the annotator recall metadata comprises a measure of the number of features within a piece of source data identified with a label in the set of annotations by the annotator; and determining annotator precision metadata based on the set of annotations provided by the annotator for the training data set using the distributed data annotation server system, where the annotator precision metadata comprises a measure of the number of correct annotations associated with each piece of source data based on the ground truth for each piece of source data; and grouping the annotators into annotator groups based on the annotator recall metadata and the annotator precision metadata using the distributed data annotation server system.
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1. A method for clustering annotators via a distributed data annotation process, comprising: obtaining a set of source data using a distributed data annotation server system, where a piece of source data in the set of source data comprises at least one identifying feature; determining a training data set representative of the set of source data using the distributed data annotation server system, where each piece of source data in the training data set comprises source data metadata describing the ground truth for the piece of source data, where the ground truth for a piece of source data describes the features contained in the piece of source data and a correct label associated with each feature; obtaining sets of annotations from a set of annotators for a portion of the training data set using the distributed data annotation server system, where an annotation identifies one or more features within a piece of source data in the training data set; for each annotator: determining annotator recall metadata based on the set of annotations provided by the annotator for the training data set using the distributed data annotation server system, where the annotator recall metadata comprises a measure of the number of features within a piece of source data identified with a label in the set of annotations by the annotator; and determining annotator precision metadata based on the set of annotations provided by the annotator for the training data set using the distributed data annotation server system, where the annotator precision metadata comprises a measure of the number of correct annotations associated with each piece of source data based on the ground truth for each piece of source data; and grouping the annotators into annotator groups based on the annotator recall metadata and the annotator precision metadata using the distributed data annotation server system. 7. The method of claim 1 , wherein the obtained sets of annotations are clustered into annotation clusters based on the features within the piece of source data identified by the annotations using the distributed data annotation server system.
| 0.521218 |
15. A non transient non-transitory computer-readable medium having stored thereon a sequence of instructions which, when loaded and executed by a processor, causes the processor to: provide a framework for creating a multi-modal dialog application in a server; include runtime media contained within a Runtime Application Package (RAP) supporting the multi-modal dialog application and configurable to perform pipeline operations on dialog during a runtime mode and files of properties associated with the runtime media in the framework, the properties including runtime and non-runtime properties for the runtime media, the RAP supporting the multi-modal dialog application created; enable customization of the RAP in the server accessible by a client via a computer network by enabling modification of the runtime media and the runtime and non-runtime properties of the runtime media via the computer network; and enable activation of the RAP customized to specialize support of the multi-modal dialog application created.
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15. A non transient non-transitory computer-readable medium having stored thereon a sequence of instructions which, when loaded and executed by a processor, causes the processor to: provide a framework for creating a multi-modal dialog application in a server; include runtime media contained within a Runtime Application Package (RAP) supporting the multi-modal dialog application and configurable to perform pipeline operations on dialog during a runtime mode and files of properties associated with the runtime media in the framework, the properties including runtime and non-runtime properties for the runtime media, the RAP supporting the multi-modal dialog application created; enable customization of the RAP in the server accessible by a client via a computer network by enabling modification of the runtime media and the runtime and non-runtime properties of the runtime media via the computer network; and enable activation of the RAP customized to specialize support of the multi-modal dialog application created. 18. The non-transitory computer-readable medium of claim 15 , wherein the non-runtime properties include properties related to inventory management, classifier training, and other ancillary services, and further wherein the runtime media includes grammars, prompts, and classifiers configured to support the multi-modal dialog application created.
| 0.520325 |
1. A method comprising: starting an automatic speech recognition session for a phone call initiated from a communication device, wherein the communication device is associated with a plurality of users; identifying, via a processor, a group of speech recognition models comprising a speaker independent model and a speaker dependent model; recognizing an utterance received from a user in the plurality of users using each model in the group of speech recognition models in parallel, to yield recognition results; selecting a dominant speech model from the group of speech recognition models using a heuristic search algorithm based on the recognition results; and continuously using the dominant speech model to recognize speech received from the user for a remainder of the automatic speech recognition session.
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1. A method comprising: starting an automatic speech recognition session for a phone call initiated from a communication device, wherein the communication device is associated with a plurality of users; identifying, via a processor, a group of speech recognition models comprising a speaker independent model and a speaker dependent model; recognizing an utterance received from a user in the plurality of users using each model in the group of speech recognition models in parallel, to yield recognition results; selecting a dominant speech model from the group of speech recognition models using a heuristic search algorithm based on the recognition results; and continuously using the dominant speech model to recognize speech received from the user for a remainder of the automatic speech recognition session. 2. The method of claim 1 , further comprising dropping a speech model from the group of speech recognition models when recognition accuracy is below a threshold.
| 0.653629 |
15. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing devices, cause: accessing metadata items that specify at least structural constraints on data objects within a data repository, the metadata items being separate from the data objects for which the metadata items specify the structural constraints; generating an index, the index mapping the metadata items to terms associated with the metadata items; generating a graph describing relationships between each of the metadata items; receiving a search request comprising at least one or more search terms; based on the one or more search terms and the index, locating a candidate set of the metadata items; performing a link analysis of the graph to determine a relationship score for each particular metadata item in at least the candidate set of metadata items; for each particular metadata item in the candidate set of the metadata items, calculating a ranking score based at least on the relationship score for the particular metadata item; generating a ranked result set based on comparing the ranking scores for the candidate set of metadata items, the ranked result set including at least one metadata item in the candidate set; providing information indicating the ranked result set in response to the search request; wherein the method is performed by one or more computing devices.
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15. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing devices, cause: accessing metadata items that specify at least structural constraints on data objects within a data repository, the metadata items being separate from the data objects for which the metadata items specify the structural constraints; generating an index, the index mapping the metadata items to terms associated with the metadata items; generating a graph describing relationships between each of the metadata items; receiving a search request comprising at least one or more search terms; based on the one or more search terms and the index, locating a candidate set of the metadata items; performing a link analysis of the graph to determine a relationship score for each particular metadata item in at least the candidate set of metadata items; for each particular metadata item in the candidate set of the metadata items, calculating a ranking score based at least on the relationship score for the particular metadata item; generating a ranked result set based on comparing the ranking scores for the candidate set of metadata items, the ranked result set including at least one metadata item in the candidate set; providing information indicating the ranked result set in response to the search request; wherein the method is performed by one or more computing devices. 27. The one or more non-transitory computer-readable media of claim 15 , wherein the instructions, when executed by the one or more computing devices, further cause: receiving definition data for a new metadata item that references a first metadata item in the result set; adding the new metadata item to the data repository; enforcing one or more constraints described by the new metadata item and the first metadata item on a particular data object within the data repository.
| 0.677008 |
11. A method of processing an encoded source document, the method comprising: receiving an encoded source document from an associated client system, the encoded source document comprising structural information and encoded content information, the encoded content information comprising a plurality of encoded tokens, the encoded tokens having been generated by individually encoding each of a plurality of text tokens of the source document to a respective value, the encoding of each of the plurality of text tokens comprising at least one of encrypting and hashing, the structural information comprising location information for each of the plurality of tokens; with a processor, processing the encoded document, without decoding the encoded tokens, to generate a modified document, the processing including modifying some of the structural information; and transmitting the modified document to an associated client system, whereby the client system is able to generate a transformed document based on the modified document and the plurality of text tokens.
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11. A method of processing an encoded source document, the method comprising: receiving an encoded source document from an associated client system, the encoded source document comprising structural information and encoded content information, the encoded content information comprising a plurality of encoded tokens, the encoded tokens having been generated by individually encoding each of a plurality of text tokens of the source document to a respective value, the encoding of each of the plurality of text tokens comprising at least one of encrypting and hashing, the structural information comprising location information for each of the plurality of tokens; with a processor, processing the encoded document, without decoding the encoded tokens, to generate a modified document, the processing including modifying some of the structural information; and transmitting the modified document to an associated client system, whereby the client system is able to generate a transformed document based on the modified document and the plurality of text tokens. 12. The method of claim 11 , further comprising providing a normalizing algorithm to the client system for normalizing the source document prior to generating the encoded source document.
| 0.618733 |
4. The apparatus of claim 1 , wherein the first cluster is a first set of one or more attributes of interest and the second cluster is a second set of attributes of interest.
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4. The apparatus of claim 1 , wherein the first cluster is a first set of one or more attributes of interest and the second cluster is a second set of attributes of interest. 7. The apparatus of claim 4 , wherein the processor is further configured to: compute a first point location of the first cluster and a second point location of the second cluster; and determine the at least one motion vector using the first point location and the second point location.
| 0.918906 |
3. The robot apparatus according to claim 1 wherein said behavior describing module varies the basic posture corresponding to said emotion depending on the size of the current emotion.
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3. The robot apparatus according to claim 1 wherein said behavior describing module varies the basic posture corresponding to said emotion depending on the size of the current emotion. 4. The robot apparatus according to claim 3 wherein the basic posture for the minimum size of the emotion and the basic posture for the maximum size thereof are stated in said behavior describing module, and wherein said behavior describing module generates the basic posture to be output by interpolating the basic posture for the minimum size of the emotion and the basic posture for the maximum size thereof, depending on the size of the current emotion as detected by said emotion management means, to generate the basic posture to be output.
| 0.766837 |
4. The apparatus of claim 1 , further including instructions that, when executed, cause the apparatus to identify an additional action to implement based on the identified risk rating.
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4. The apparatus of claim 1 , further including instructions that, when executed, cause the apparatus to identify an additional action to implement based on the identified risk rating. 5. The apparatus of claim 4 , wherein the additional action includes altering access to information available to a user associated with the string of terms.
| 0.957051 |
12. A method of managing information comprising: providing an organization having an information management system comprising one or more rules comprising a context expression stored on a server to manage information of the organization; within the organization, providing a user logged onto a client and a confidential document managed by the information management system; storing a subset of the one or more rules of the policy on the client, wherein the subset of one or more rules of the policy are supported by the client and a first rule of the subset of one or more rules comprises translating the first rule from a first syntax format not supported by the client to a second syntax format supported by the client; when the user attempts to perform an operation on the confidential document, evaluating the one or more rules at the client only to determine whether to store information regarding the attempted operation in a storage location, wherein based on a first context expression of a first rule, approving the attempted operation will occur only during a particular time period, and based on a second context expression of a second rule, approving the attempted operation will occur only when the user is in a particular location; after the evaluating, updating the one or more rules at the client with the rules stored at the server with one or more updated rules; and after the updating, when the user attempts to perform the operation on the confidential document, evaluating the one or more updated rules at the client only.
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12. A method of managing information comprising: providing an organization having an information management system comprising one or more rules comprising a context expression stored on a server to manage information of the organization; within the organization, providing a user logged onto a client and a confidential document managed by the information management system; storing a subset of the one or more rules of the policy on the client, wherein the subset of one or more rules of the policy are supported by the client and a first rule of the subset of one or more rules comprises translating the first rule from a first syntax format not supported by the client to a second syntax format supported by the client; when the user attempts to perform an operation on the confidential document, evaluating the one or more rules at the client only to determine whether to store information regarding the attempted operation in a storage location, wherein based on a first context expression of a first rule, approving the attempted operation will occur only during a particular time period, and based on a second context expression of a second rule, approving the attempted operation will occur only when the user is in a particular location; after the evaluating, updating the one or more rules at the client with the rules stored at the server with one or more updated rules; and after the updating, when the user attempts to perform the operation on the confidential document, evaluating the one or more updated rules at the client only. 17. The method of claim 12 wherein the when the user attempts to perform an operation on the confidential document, evaluating the one or more rules to determine whether to store information regarding the attempted operation in a storage location is replaced by when the user performs an operation on the confidential document, evaluating the one or more rules to determine whether to store information regarding the operation in a storage location.
| 0.644681 |
23. A non-transitory computer readable medium storing a computer-executable module, the computer-executable module, when executed by one or more processors, causing the one or more processors to perform a process comprising: generating a lattice comprising a plurality of recognition hypotheses for acoustic model training data, wherein the acoustic model training data is associated with a transcription, wherein the transcription comprises a sequence of one or more transcribed subword units, wherein a first path through the lattice comprises a first sequence of one or more recognized subword units, wherein each transcribed subword unit of the sequence of transcribed subword units comprises one of a plurality of language subword units, and wherein each recognized subword unit of the sequence of recognized subword units comprises one of the plurality of language subword units; calculating a substitution probability that a first language subword unit is substituted by a second language subword unit based at least in part on a comparison of the first sequence of one or more recognized subword units to the sequence of one or more transcribed subword units; generating a confusion matrix using the substitution probability, wherein the confusion matrix comprises a plurality of substitution probabilities; updating language model training data to generate updated language model training data, wherein updating the language model training data comprises adding an alternate transcription based at least partly on the transcription and the confusion matrix; and discriminatively training a language model using the updated language model training data.
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23. A non-transitory computer readable medium storing a computer-executable module, the computer-executable module, when executed by one or more processors, causing the one or more processors to perform a process comprising: generating a lattice comprising a plurality of recognition hypotheses for acoustic model training data, wherein the acoustic model training data is associated with a transcription, wherein the transcription comprises a sequence of one or more transcribed subword units, wherein a first path through the lattice comprises a first sequence of one or more recognized subword units, wherein each transcribed subword unit of the sequence of transcribed subword units comprises one of a plurality of language subword units, and wherein each recognized subword unit of the sequence of recognized subword units comprises one of the plurality of language subword units; calculating a substitution probability that a first language subword unit is substituted by a second language subword unit based at least in part on a comparison of the first sequence of one or more recognized subword units to the sequence of one or more transcribed subword units; generating a confusion matrix using the substitution probability, wherein the confusion matrix comprises a plurality of substitution probabilities; updating language model training data to generate updated language model training data, wherein updating the language model training data comprises adding an alternate transcription based at least partly on the transcription and the confusion matrix; and discriminatively training a language model using the updated language model training data. 30. The non-transitory computer readable medium of claim 23 , wherein the updated training data comprises the transcription, and wherein the alternate transcription comprises the transcription with a substitution of the second language subword unit for the first language subword unit.
| 0.682041 |
9. The method of claim 6 , wherein the query contains a correlation predicate.
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9. The method of claim 6 , wherein the query contains a correlation predicate. 10. The method of claim 9 , further comprising: translating the correlation predicate into a join predicate in a context of the outlier materialized query table; when the translated join predicate matches the join predicate in the outlier materialized query table, deriving a new predicate for the correlation predicate in a child query block using a source predicate on a quantifier of a parent query block; and wherein searching the query for the source predicate further includes searching the parent query block for the source predicate.
| 0.886278 |
5. The method of claim 1 , wherein the applying the system analysis function to the set of data elements to characterize the at least one dataset specification associated with the set of data elements comprises: applying, by the host device, a clustering function to the each data element of the set of data elements to define a set of clusters; and providing, by the host device, an assigned dataset specification to each cluster of the set of clusters.
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5. The method of claim 1 , wherein the applying the system analysis function to the set of data elements to characterize the at least one dataset specification associated with the set of data elements comprises: applying, by the host device, a clustering function to the each data element of the set of data elements to define a set of clusters; and providing, by the host device, an assigned dataset specification to each cluster of the set of clusters. 7. The method of claim 5 , wherein the receiving the user-selected policy threshold criterion identifying the dataset specification of the at least one dataset specification further comprises applying, by the host device, the user-selected policy threshold to the system analysis function to generate a semi-supervised function.
| 0.829332 |
1. A method comprising: executing an application at a device, wherein context data including context data items is associated with the executing application; selecting a messaging technology to send a message from the device; selecting a template for the message, wherein the template comprises a dynamic field; selecting a context data item from the context data associated with the executing application; and automatically inserting the selected context data item in the dynamic field to facilitate the creation of a message.
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1. A method comprising: executing an application at a device, wherein context data including context data items is associated with the executing application; selecting a messaging technology to send a message from the device; selecting a template for the message, wherein the template comprises a dynamic field; selecting a context data item from the context data associated with the executing application; and automatically inserting the selected context data item in the dynamic field to facilitate the creation of a message. 2. The method of claim 1 , further comprising sending the message to a device using the selected messaging technology.
| 0.641388 |
14. The method of claim 1 , applying the second set of rules resulting in assigning respective scores to respective groups of name segments, the computer determining whether the on-line bank account is utilized for business purposes based at least in part upon the respective scores for respective groups of name segments.
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14. The method of claim 1 , applying the second set of rules resulting in assigning respective scores to respective groups of name segments, the computer determining whether the on-line bank account is utilized for business purposes based at least in part upon the respective scores for respective groups of name segments. 18. The method of claim 14 , the second set of rules comprising a rule that assigns a score to a group of name segments based on a location of a first name segment relative to at least one other name segment in the group.
| 0.82992 |
1. A computer-implemented method for predicting an opinion, the computer-implemented method comprising: building a corpus which includes a first collection of documents attributable to a first person and a second collection of documents not attributable to the first person, wherein the second collection of documents is identified from content in the first collection of documents, wherein each of the second collection of documents is available from a respective secondary source; evaluating the corpus to build a model representing opinions of the first person relative to topics, concepts, or subjects discussed in the first and second collections of documents, including determining, for each secondary source, a source weight factor characterizing a presumed opinion of the secondary source held by the first person; receiving a request to predict an opinion of the first person regarding a topic specified in the request; generating a predicted opinion of the first person regarding the topic from the model, by operation of one or more computer processors and based on: (i) the opinions of the first person relative to topics, concepts, or subjects discussed in the first and second collections of documents and (ii) each source weight factor characterizing the presumed opinion of the respective secondary source held by the first person; and returning the predicted opinion responsive to the request.
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1. A computer-implemented method for predicting an opinion, the computer-implemented method comprising: building a corpus which includes a first collection of documents attributable to a first person and a second collection of documents not attributable to the first person, wherein the second collection of documents is identified from content in the first collection of documents, wherein each of the second collection of documents is available from a respective secondary source; evaluating the corpus to build a model representing opinions of the first person relative to topics, concepts, or subjects discussed in the first and second collections of documents, including determining, for each secondary source, a source weight factor characterizing a presumed opinion of the secondary source held by the first person; receiving a request to predict an opinion of the first person regarding a topic specified in the request; generating a predicted opinion of the first person regarding the topic from the model, by operation of one or more computer processors and based on: (i) the opinions of the first person relative to topics, concepts, or subjects discussed in the first and second collections of documents and (ii) each source weight factor characterizing the presumed opinion of the respective secondary source held by the first person; and returning the predicted opinion responsive to the request. 15. The computer-implemented method of claim 1 , wherein building the corpus comprises: parsing the first collection of documents to identify secondary sources.
| 0.571933 |
1. A method comprising: receiving, at a computing device, a request to display information related to a first physical entity; transforming, via the computing device, the request into search data; dynamically applying, via the computing device, the search data to descriptive information related to a set of other physical entities known to a network, said application of the search data comprising deriving a subset of other physical entities matching the search data from the descriptive information related to the set of other known physical entities, the descriptive information corresponding to the other physical entities is analyzed as part of said deriving the subset of other physical entities that match the search data; ranking, via the computing device, the physical entities in the subset of other physical entities to form a ranked subset of physical entities, the ranked subset based upon the applied search data, the ranked subset comprising the descriptive information corresponding to the other physical entities of the subset; and presenting, via the computing device over the network, information related to the ranked subset of physical entities to a first user associated with a user computing device, the presenting of the ranked physical entities information being dependent upon user information stored in the network, the user information comprising data generated by the user, data associated with the user, and data associated with the request.
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1. A method comprising: receiving, at a computing device, a request to display information related to a first physical entity; transforming, via the computing device, the request into search data; dynamically applying, via the computing device, the search data to descriptive information related to a set of other physical entities known to a network, said application of the search data comprising deriving a subset of other physical entities matching the search data from the descriptive information related to the set of other known physical entities, the descriptive information corresponding to the other physical entities is analyzed as part of said deriving the subset of other physical entities that match the search data; ranking, via the computing device, the physical entities in the subset of other physical entities to form a ranked subset of physical entities, the ranked subset based upon the applied search data, the ranked subset comprising the descriptive information corresponding to the other physical entities of the subset; and presenting, via the computing device over the network, information related to the ranked subset of physical entities to a first user associated with a user computing device, the presenting of the ranked physical entities information being dependent upon user information stored in the network, the user information comprising data generated by the user, data associated with the user, and data associated with the request. 4. The method of claim 1 wherein the presenting of the ranked physical entities information is dependent upon data associated with the user's location.
| 0.654158 |
7. A computer program product embodied in a tangible media comprising: computer readable program codes coupled to the tangible media for enabling parametric searches on source data, using text search engine, the computer readable program codes configured to cause the program to: extract at least one numeric data unit from the source data; automatically translate the numeric data unit into at least one keyword parametric entry; store the keyword parametric entry in a surrogate document at a search engine server; receive a parametric query from a client, the parametric query forming an attribute-value pair; translate the parametric query into at least one keyword search entry, the keyword search entry forming at least one attribute-operator-interval triplet based on the parametric query; search the surrogate document for the keyword search entry; and submit to the client at least one result of searching the surrogate document for the keyword search entry; and wherein the computer readable program code to translate the parametric query into at least one keyword search entry further comprises computer readable program code to determine at least one search interval; and wherein the operator is based on the search interval.
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7. A computer program product embodied in a tangible media comprising: computer readable program codes coupled to the tangible media for enabling parametric searches on source data, using text search engine, the computer readable program codes configured to cause the program to: extract at least one numeric data unit from the source data; automatically translate the numeric data unit into at least one keyword parametric entry; store the keyword parametric entry in a surrogate document at a search engine server; receive a parametric query from a client, the parametric query forming an attribute-value pair; translate the parametric query into at least one keyword search entry, the keyword search entry forming at least one attribute-operator-interval triplet based on the parametric query; search the surrogate document for the keyword search entry; and submit to the client at least one result of searching the surrogate document for the keyword search entry; and wherein the computer readable program code to translate the parametric query into at least one keyword search entry further comprises computer readable program code to determine at least one search interval; and wherein the operator is based on the search interval. 8. The computer program product of claim 7 , wherein the computer readable program code to translate the parametric query into at least one keyword search entry further comprises computer readable program code to determine at least one search interval.
| 0.525124 |
1. A system for search engine optimization, comprising: several modules comprising smart tools that provide isolation and workflow collaboration of tools in a search engine optimization (SEO) suite; a first smart tool using log files for key-wordless rank checking; a second smart tool using log files for hyperlink analysis; a third smart tool identifying web authorities for competitive analysis; a fourth smart tool providing live relevancy metrics in on-page optimization editor; a fifth smart tool rotating authorization code to prevent usage of a software license in more than one computer; wherein more incoming links for a user website are extracted than querying search engines directly; wherein processing of website log files to identify every single internal page on the user website and external pages that are linking to each internal page; wherein an identification of every single internal page on the user website and external pages that are linking to each internal page is present in a referrer log file; and wherein extracted hyperlink information is used to identify link rich pages and link poor pages, wherein the link poor pages are less likely to be included in search engines index than the link rich pages.
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1. A system for search engine optimization, comprising: several modules comprising smart tools that provide isolation and workflow collaboration of tools in a search engine optimization (SEO) suite; a first smart tool using log files for key-wordless rank checking; a second smart tool using log files for hyperlink analysis; a third smart tool identifying web authorities for competitive analysis; a fourth smart tool providing live relevancy metrics in on-page optimization editor; a fifth smart tool rotating authorization code to prevent usage of a software license in more than one computer; wherein more incoming links for a user website are extracted than querying search engines directly; wherein processing of website log files to identify every single internal page on the user website and external pages that are linking to each internal page; wherein an identification of every single internal page on the user website and external pages that are linking to each internal page is present in a referrer log file; and wherein extracted hyperlink information is used to identify link rich pages and link poor pages, wherein the link poor pages are less likely to be included in search engines index than the link rich pages. 3. The system for search engine optimization of claim 1 , wherein the first smart tool using log files for key-wordless rank checking in an SEO tool further comprises: a site URL and a web server log file for the site that corresponds with the URL to be provided; otherwise, the first smart tool will automatically detect the URL from a plurality of referrers in the log files; and software that discovers keywords and search engines users are using to find a user site by detecting a search engine result page, by studying one of the plurality of referrers information in the log files.
| 0.623188 |
4. The method of claim 1 , further comprising: calculating memory usage statistics, the calculating including at least determining a shallow heap; and determining retained heap usages by traversing through dependency trees of the heap dump.
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4. The method of claim 1 , further comprising: calculating memory usage statistics, the calculating including at least determining a shallow heap; and determining retained heap usages by traversing through dependency trees of the heap dump. 6. The method of claim 4 , where the shallow and retained heaps are grouped together by class to calculate the shallow and retained heaps of entire classes along with the number of objects created for each class; and where each class is analyzed for memory leaks or excessive memory usage.
| 0.833204 |
1. A computer-implemented method comprising: identifying, by a server system comprising one or more computers, first terms based on an evaluation of a web page; identifying, by the server system, one or more related resources that are associated with the first terms, and identifying, for each related resource, one or more second terms associated with the related resource based on an evaluation of the related resource; associating, by the server system, each of (i) the first terms identified based on the evaluation of the web page and (ii) the one or more second terms respectively associated with the one or more related resources with a respective node in a directed graph; providing, by the server system, one or more connections between the nodes in the directed graph, wherein the one or more connections indicate magnitudes and directions that represent one or more relationships between (i) the first terms identified based on the evaluation of the web page, and (ii) the one or more second terms respectively associated with the one or more related resources; selecting, by the server system, a subset of the first terms based on the connections representing the one or more relationships between (i) the first terms identified based on the evaluation of the web page, and (ii) the one or more second terms respectively associated with the one or more related resources; associating, by the server system, the selected subset of the first terms with the web page; storing, by the server system and in a database, data that indicates that the selected subset of the first terms are associated with the web page; selecting, by the server system, a knowledge item from among a plurality of knowledge items based on the selected subset of the first terms that the database indicates are associated with the web page; and providing, by the server system, the selected knowledge item for display with the web page at a client device.
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1. A computer-implemented method comprising: identifying, by a server system comprising one or more computers, first terms based on an evaluation of a web page; identifying, by the server system, one or more related resources that are associated with the first terms, and identifying, for each related resource, one or more second terms associated with the related resource based on an evaluation of the related resource; associating, by the server system, each of (i) the first terms identified based on the evaluation of the web page and (ii) the one or more second terms respectively associated with the one or more related resources with a respective node in a directed graph; providing, by the server system, one or more connections between the nodes in the directed graph, wherein the one or more connections indicate magnitudes and directions that represent one or more relationships between (i) the first terms identified based on the evaluation of the web page, and (ii) the one or more second terms respectively associated with the one or more related resources; selecting, by the server system, a subset of the first terms based on the connections representing the one or more relationships between (i) the first terms identified based on the evaluation of the web page, and (ii) the one or more second terms respectively associated with the one or more related resources; associating, by the server system, the selected subset of the first terms with the web page; storing, by the server system and in a database, data that indicates that the selected subset of the first terms are associated with the web page; selecting, by the server system, a knowledge item from among a plurality of knowledge items based on the selected subset of the first terms that the database indicates are associated with the web page; and providing, by the server system, the selected knowledge item for display with the web page at a client device. 7. The method of claim 1 , wherein selecting a subset of the first terms comprises selecting first terms that are each also associated with the related resources by more than a predetermined degree.
| 0.880265 |
1. An apparatus, comprising: a device including at least one input device, at least one display, and memory in communication with at least one hardware processor; and a browser installed on the memory of the device for allowing access, utilizing the at least one input device and the at least one hardware processor, to a system including a hardware server, the system configured for: identifying at least parts of a plurality of original documents including a plurality of original values, the plurality of original documents including a first document including first values and a second document including second values; processing at least a part of the first document and at least a part of the second document, resulting in at least one data structure including at least one of the plurality of original values of at least one of the plurality of original documents; receiving one or more indications for one or more of the original values for adding, in connection with at least one computer-readable Extensible Markup Language (XML)-compliant data document, a corresponding one or more computer-readable semantic tags in association with the one or more original values; associating the one or more computer-readable semantic tags with the one or more original values such that the one or more computer-readable semantic tags are each computer-readably associated with the one or more original values; causing output of a presentation that is based on at least a portion of the at least one data structure, the presentation capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the presentation; causing output of a report that is based on at least a portion of the at least one data structure, the report capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the report; and causing output of the computer-readable XML-compliant data document that is based on at least a portion of at least one data structure, the at least one computer-readable XML-compliant data document capable of including a plurality of line items at least one of which utilizes at least a portion of the original values including the at least one original value and at least some of the one or more computer-readable semantic tags, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the at least one computer-readable XML-compliant data document; said apparatus configured for: receiving user input utilizing the browser, and displaying the at least one computer-readable XML-compliant data document utilizing the browser, after the user input.
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1. An apparatus, comprising: a device including at least one input device, at least one display, and memory in communication with at least one hardware processor; and a browser installed on the memory of the device for allowing access, utilizing the at least one input device and the at least one hardware processor, to a system including a hardware server, the system configured for: identifying at least parts of a plurality of original documents including a plurality of original values, the plurality of original documents including a first document including first values and a second document including second values; processing at least a part of the first document and at least a part of the second document, resulting in at least one data structure including at least one of the plurality of original values of at least one of the plurality of original documents; receiving one or more indications for one or more of the original values for adding, in connection with at least one computer-readable Extensible Markup Language (XML)-compliant data document, a corresponding one or more computer-readable semantic tags in association with the one or more original values; associating the one or more computer-readable semantic tags with the one or more original values such that the one or more computer-readable semantic tags are each computer-readably associated with the one or more original values; causing output of a presentation that is based on at least a portion of the at least one data structure, the presentation capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the presentation; causing output of a report that is based on at least a portion of the at least one data structure, the report capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the report; and causing output of the computer-readable XML-compliant data document that is based on at least a portion of at least one data structure, the at least one computer-readable XML-compliant data document capable of including a plurality of line items at least one of which utilizes at least a portion of the original values including the at least one original value and at least some of the one or more computer-readable semantic tags, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the at least one computer-readable XML-compliant data document; said apparatus configured for: receiving user input utilizing the browser, and displaying the at least one computer-readable XML-compliant data document utilizing the browser, after the user input. 19. The apparatus of claim 1 , wherein the system is configured such that at least a part of the one or more computer-readable semantic tags describe a semantic meaning of at least part of the original values via a computer-readable association between each of the at least part of the one or more computer-readable semantic tags and a corresponding line item, and not directly between the at least part of the one or more computer-readable semantic tags and the at least part of the original values themselves.
| 0.743846 |
8. The method of claim 1 , wherein processing the set of previously scored training submissions comprises automatically identifying question-asker-assigned ratings of one or more of the previously scored training submissions, wherein identifying the question-asker-assigned ratings comprises identifying question-asker-assigned ratings that are correlated with the scores that one or more of the previously scored training submissions received.
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8. The method of claim 1 , wherein processing the set of previously scored training submissions comprises automatically identifying question-asker-assigned ratings of one or more of the previously scored training submissions, wherein identifying the question-asker-assigned ratings comprises identifying question-asker-assigned ratings that are correlated with the scores that one or more of the previously scored training submissions received. 21. A volatile or non-volatile computer-readable storage medium that stores instructions which, when executed by one or more processors, cause the one or more processors to perform the method of claim 8 .
| 0.882637 |
15. A system, comprising: a software engine stored on a computer-readable media which has executable instructions, which when executed by a machine, cause the machine to perform operations, wherein the engine further includes an intelligence layer having code to analyze content in an active desktop window and to generate a set of most relevant terms and mathematical values associated with those relevant terms from the content in the active desktop window; a query handler having code to generate a query on the content from an active desktop window and to initiate a search on content in one or more documents based on at least the set of most relevant terms and mathematical values associated with those relevant terms from the content in the active desktop window; wherein the intelligence layer has code to generate a ranked list of documents related to the content in one or more documents based on relevance to at least the set of most relevant terms and mathematical values associated with those relevant terms from the content in the active desktop window, and has code to generate links to the ranked list of documents, wherein the links point to one or more relevant fields within the ranked list of documents, wherein the intelligence layer has code to analyze content in the active desktop window and generate the ranked list and generate the links without a user having to request any of these operations, wherein the query handler has code to the generate the query and initiate the search without a user having to request any of these operations; and computing device having a display to display the generated ranked list of documents on the display.
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15. A system, comprising: a software engine stored on a computer-readable media which has executable instructions, which when executed by a machine, cause the machine to perform operations, wherein the engine further includes an intelligence layer having code to analyze content in an active desktop window and to generate a set of most relevant terms and mathematical values associated with those relevant terms from the content in the active desktop window; a query handler having code to generate a query on the content from an active desktop window and to initiate a search on content in one or more documents based on at least the set of most relevant terms and mathematical values associated with those relevant terms from the content in the active desktop window; wherein the intelligence layer has code to generate a ranked list of documents related to the content in one or more documents based on relevance to at least the set of most relevant terms and mathematical values associated with those relevant terms from the content in the active desktop window, and has code to generate links to the ranked list of documents, wherein the links point to one or more relevant fields within the ranked list of documents, wherein the intelligence layer has code to analyze content in the active desktop window and generate the ranked list and generate the links without a user having to request any of these operations, wherein the query handler has code to the generate the query and initiate the search without a user having to request any of these operations; and computing device having a display to display the generated ranked list of documents on the display. 16. The system of claim 15 , wherein the software engine further comprises: a reconciler module and a hierarchical module to cooperate with the intelligence layer to create a first representation of the content from the active desktop window for the query by performing at least the following, eliminating redundant terms in a corpus of terms contained within the content by using a first algorithm to generate an initial set of most relevant terms; refining the initial set of most relevant terms by determining a statistical relevance and relational probability between the terms for each term in the initial set of most relevant terms to create the set of most relevant terms; determining one or more weighted values with each term in the set of most relevant terms; generating a structure for the first representation content in the active desktop window to contain the set of most relevant terms from the content and the one or more weighted values associated with each term in the set of most relevant terms; and inserting an additional extensible markup language tag-value pair into the first representation while allowing the first representation to keep its original tag value pair nomenclature from its original extensible markup language schema to establish a common extensible markup language schema with representations derived from content in documents having a different extensible markup language schema than the original extensible markup language schema for the first representation.
| 0.506024 |
19. The system of claim 14 , wherein the instructions to provide the additional information include instructions to provide a notification to the sender and wherein the sender is the creator of the message.
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19. The system of claim 14 , wherein the instructions to provide the additional information include instructions to provide a notification to the sender and wherein the sender is the creator of the message. 20. The system of claim 19 , wherein the notification includes a prompt for the sender to grant permission to allow the providing of the additional information.
| 0.93244 |
19. The at least one tangible computer readable storage medium of claim 16 , the method further comprising: calculating grammar generation statistics in order to provide optimization advice for future grammar file generation.
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19. The at least one tangible computer readable storage medium of claim 16 , the method further comprising: calculating grammar generation statistics in order to provide optimization advice for future grammar file generation. 20. The at least one tangible computer readable storage medium of claim 19 , wherein the optimization advice is based on voice recognition engine capabilities.
| 0.902855 |
10. A method for processing text on a computer with a storage for storing a text string comprised of a plurality of characters each having a character code, and a display for displaying each character in said plurality of characters in a font selected from a plurality of fonts stored in said storage in an indexed font table containing glyphs for each of said plurality of fonts, said method comprising the steps of: (a) selecting a first font from said plurality of fonts stored in said storage; (b) inputting into said computer a character code representative of a particular character to be inserted into said text string at an insertion point; (c) determining if said character code is defined in said first font by accessing said indexed font table utilizing said character code as an index to determine if there is a first associated glyph for said first font, and if a first associated glyph is found, then displaying said particular character in said first font by displaying said first associated glyph on said display; (d) selecting other fonts in said ordered font table which other fonts are used to display at least one of said plurality of characters in said text string if said particular character does not have a first associated glyph in said first font; (e) utilizing said character code as an index to determine if there is a second associated glyph in said ordered font table for said other fonts and if a second associated glyph is found, then displaying said particular character by displaying said second associated glyph on said display; and (f) displaying a predetermined third glyph from a default font if a second associated glyph is not found.
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10. A method for processing text on a computer with a storage for storing a text string comprised of a plurality of characters each having a character code, and a display for displaying each character in said plurality of characters in a font selected from a plurality of fonts stored in said storage in an indexed font table containing glyphs for each of said plurality of fonts, said method comprising the steps of: (a) selecting a first font from said plurality of fonts stored in said storage; (b) inputting into said computer a character code representative of a particular character to be inserted into said text string at an insertion point; (c) determining if said character code is defined in said first font by accessing said indexed font table utilizing said character code as an index to determine if there is a first associated glyph for said first font, and if a first associated glyph is found, then displaying said particular character in said first font by displaying said first associated glyph on said display; (d) selecting other fonts in said ordered font table which other fonts are used to display at least one of said plurality of characters in said text string if said particular character does not have a first associated glyph in said first font; (e) utilizing said character code as an index to determine if there is a second associated glyph in said ordered font table for said other fonts and if a second associated glyph is found, then displaying said particular character by displaying said second associated glyph on said display; and (f) displaying a predetermined third glyph from a default font if a second associated glyph is not found. 13. The method as recited in claim 10, wherein step (d) comprises the steps of: (d1) selecting a test character from said plurality of characters in said text string which test character precedes said insertion point; (d2) selecting a second font from said plurality of fonts stored in said storage, which second font is used to display said test character; (d3) determining if said particular character can be displayed in said second font by searching said ordered font table utilizing said character code as an index to determine if there is a second associated glyph for said second font, and if a second associated glyph is found, then displaying said particular character in said second font by displaying said second associated glyph on said display; and (d4) selecting another test character from said plurality of characters in said text string which other test character precedes said insertion point if said particular character does not have an associated glyph in said second font, and repeating steps (d1) to (d3) for said other test character until all characters preceding the insertion point have been tested.
| 0.5 |
11. At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one server comprising a computer hardware processor, cause the at least one server to perform a method comprising: receiving, at the server, a representation of a voice utterance received by an application program executing on a client device; recognizing, using an automated speech recognition (ASR) engine executing at the server, the voice utterance to obtain a recognition result, the recognizing comprising: obtaining, based on the voice utterance, a language segment sequence comprising one or more language segments in a vocabulary of language segments; accessing an unnormalized neural network language model having a normalizer node and an output layer comprising a plurality of output nodes, each of the plurality of output nodes associated with a respective language segment in the vocabulary, wherein the plurality of output nodes includes a first output node associated with the first language segment in the vocabulary; determining the recognition result at least in part by determining, using the unnormalized neural network language model, a first likelihood that a first language segment in the vocabulary follows the language segment sequence, wherein determining the first likelihood comprises: determining, based at least in part on features derived from the language segment sequence, an output score for the first output node; determining, based at least in part on the features, an output score for the normalizer node; and determining the first likelihood based on the output score for the first output node and the output score for the normalizer node, wherein determining the first likelihood that the first language segment in the vocabulary follows the language segment sequence is performed independently of output scores of any output nodes, other than the first output node, in the plurality of output nodes; and providing, by the server, the recognition result to the application program executing on the client device.
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11. At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one server comprising a computer hardware processor, cause the at least one server to perform a method comprising: receiving, at the server, a representation of a voice utterance received by an application program executing on a client device; recognizing, using an automated speech recognition (ASR) engine executing at the server, the voice utterance to obtain a recognition result, the recognizing comprising: obtaining, based on the voice utterance, a language segment sequence comprising one or more language segments in a vocabulary of language segments; accessing an unnormalized neural network language model having a normalizer node and an output layer comprising a plurality of output nodes, each of the plurality of output nodes associated with a respective language segment in the vocabulary, wherein the plurality of output nodes includes a first output node associated with the first language segment in the vocabulary; determining the recognition result at least in part by determining, using the unnormalized neural network language model, a first likelihood that a first language segment in the vocabulary follows the language segment sequence, wherein determining the first likelihood comprises: determining, based at least in part on features derived from the language segment sequence, an output score for the first output node; determining, based at least in part on the features, an output score for the normalizer node; and determining the first likelihood based on the output score for the first output node and the output score for the normalizer node, wherein determining the first likelihood that the first language segment in the vocabulary follows the language segment sequence is performed independently of output scores of any output nodes, other than the first output node, in the plurality of output nodes; and providing, by the server, the recognition result to the application program executing on the client device. 12. The at least one non-transitory computer-readable storage medium of claim 11 , wherein the output score for the normalizer node is an estimate of a sum of output scores of output nodes in the plurality of output nodes.
| 0.693243 |
5. Apparatus according to claim 4 wherein the displayed figures define a plurality of areas of overlap within each of which the results delivered are for the core search query and a suggested query.
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5. Apparatus according to claim 4 wherein the displayed figures define a plurality of areas of overlap within each of which the results delivered are for the core search query and a suggested query. 8. Apparatus according to claim 5 further comprising said instructions when executing on said processor being effective to respond to the system user pointing a screen cursor to an area of overlap outside of the core query figure by displaying results delivered by the search program which exclude the core query.
| 0.843582 |
15. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: determining that a sponsored content item has been identified as likely containing malware; identifying features of a landing page of the sponsored content item that has been identified as likely containing malware, wherein the sponsored content item directs a content viewer to the landing page in response to a selection of the sponsored content item; identifying features of another landing page of another sponsored content item that has not been identified as likely containing malware; determining that the features of the landing page of the sponsored content item that has been identified as likely containing malware are similar or identical to the features of the other landing page of the other sponsored content item that has not been identified as likely containing malware; and based on determining that the features of the landing page of the sponsored content item that has been identified as likely containing malware are similar or identical to the features of the other landing page of the other sponsored content item that has not been identified as likely containing malware, suspending distribution of the other sponsored content item that has not been identified as likely containing malware.
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15. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: determining that a sponsored content item has been identified as likely containing malware; identifying features of a landing page of the sponsored content item that has been identified as likely containing malware, wherein the sponsored content item directs a content viewer to the landing page in response to a selection of the sponsored content item; identifying features of another landing page of another sponsored content item that has not been identified as likely containing malware; determining that the features of the landing page of the sponsored content item that has been identified as likely containing malware are similar or identical to the features of the other landing page of the other sponsored content item that has not been identified as likely containing malware; and based on determining that the features of the landing page of the sponsored content item that has been identified as likely containing malware are similar or identical to the features of the other landing page of the other sponsored content item that has not been identified as likely containing malware, suspending distribution of the other sponsored content item that has not been identified as likely containing malware. 19. The medium of claim 15 , the operations comprising, after suspending distribution of the other sponsored content item that has not been identified as likely containing malware, determining that the other sponsored content item is free from malware, and resuming distribution of the other sponsored content item.
| 0.635277 |
1. A computer-implemented method comprising: receiving, by a given mobile device, audio data corresponding to a user utterance; while receiving the audio data corresponding to the user utterance, determining, by the given mobile device, that the given mobile device has changed position from a first pose to a second pose; in response to determining that the given mobile device has changed position from the first pose to the second pose, determining endpointing parameters for endpointing audio data received by a mobile device changing from the first pose to the second pose; using the endpointing parameters for endpointing audio data received by a mobile device changing from the first pose to the second pose, endpointing the received audio data; generating, by an automated speech recognizer, a transcription of the endpointed audio data; and providing, for output by the given mobile device, the transcription.
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1. A computer-implemented method comprising: receiving, by a given mobile device, audio data corresponding to a user utterance; while receiving the audio data corresponding to the user utterance, determining, by the given mobile device, that the given mobile device has changed position from a first pose to a second pose; in response to determining that the given mobile device has changed position from the first pose to the second pose, determining endpointing parameters for endpointing audio data received by a mobile device changing from the first pose to the second pose; using the endpointing parameters for endpointing audio data received by a mobile device changing from the first pose to the second pose, endpointing the received audio data; generating, by an automated speech recognizer, a transcription of the endpointed audio data; and providing, for output by the given mobile device, the transcription. 3. The method of claim 1 , wherein determining that the given mobile device has changed position from a first pose to a second pose comprises: determining that a distance between the given mobile device and a user of the mobile device has changed from a first distance to a second distance.
| 0.859556 |
27. The program storage device of claim 26, for performing an exact search, comprising the steps of: associating specified data to one of the clusters based on stored clustering information; decomposing the specified data into a reduced dimensionality cluster defined by an associated cluster and stored dimensionality reduction information for the associated cluster, in response to said associating; and searching said indexes for a matching reduced dimensionality cluster based on decomposed specified data.
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27. The program storage device of claim 26, for performing an exact search, comprising the steps of: associating specified data to one of the clusters based on stored clustering information; decomposing the specified data into a reduced dimensionality cluster defined by an associated cluster and stored dimensionality reduction information for the associated cluster, in response to said associating; and searching said indexes for a matching reduced dimensionality cluster based on decomposed specified data. 28. The program storage device of claim 27, wherein the query includes a search template, further comprising the steps of: said associating comprising identifying the search template with a cluster based on the stored clustering information; said decomposing comprising projecting the search template onto a subspace for an identified cluster based on the stored dimensionality reduction information; and said searching comprising performing an intra-cluster search for a projected template.
| 0.875 |
7. A method for suggesting messages in a social dating system, comprising: receiving a request from a user device associated with a viewing user to view a matching user; identifying a common interest representing a general interest in common between the viewing user and the matching user based on interactions of the viewing user with a first social networking object for a first specific interest and interactions by the matching user with a second social networking object for a second specific interest, where the first and second social networking objects are different; selecting a promotional offer for the viewing user for an activity to do with the matching user related to the identified common interest; and transmitting the promotional offer to the user device for display.
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7. A method for suggesting messages in a social dating system, comprising: receiving a request from a user device associated with a viewing user to view a matching user; identifying a common interest representing a general interest in common between the viewing user and the matching user based on interactions of the viewing user with a first social networking object for a first specific interest and interactions by the matching user with a second social networking object for a second specific interest, where the first and second social networking objects are different; selecting a promotional offer for the viewing user for an activity to do with the matching user related to the identified common interest; and transmitting the promotional offer to the user device for display. 11. The method of claim 7 , wherein the promotional offer is sent to another user device associated with the matching user.
| 0.689642 |
18. System providing controlled disclosure of facts to a first entity by a second entity, comprising: said first entity in communication with a transmission medium, said first entity comprising a first processing module transmitting a request for publication of a first fact over said transmission medium, wherein said first fact is related to said second entity; and said second entity in communication with said transmission medium, receiving said request for said first fact from said first entity, said second entity comprising: a memory module storing a plurality of facts including said first fact, each of said plurality of facts having an indicia of authorization for publication of each of said plurality of facts; and a second processing module in communication with said memory module, for determining whether said indicia of authorization for said first fact permits publication of said first fact to said first entity, and disclosing said first fact to said first entity when said indicia of authorization permits publication of said first fact.
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18. System providing controlled disclosure of facts to a first entity by a second entity, comprising: said first entity in communication with a transmission medium, said first entity comprising a first processing module transmitting a request for publication of a first fact over said transmission medium, wherein said first fact is related to said second entity; and said second entity in communication with said transmission medium, receiving said request for said first fact from said first entity, said second entity comprising: a memory module storing a plurality of facts including said first fact, each of said plurality of facts having an indicia of authorization for publication of each of said plurality of facts; and a second processing module in communication with said memory module, for determining whether said indicia of authorization for said first fact permits publication of said first fact to said first entity, and disclosing said first fact to said first entity when said indicia of authorization permits publication of said first fact. 22. The system according to claim 18, further comprising: a third entity in communication with said transmission medium, said third entity revealing each of said plurality of facts to said second entity.
| 0.735426 |
14. The method of claim 1 , further comprising generating a prompt for additional input, based on the conclusion, the prompt included in a rendering of the structured document.
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14. The method of claim 1 , further comprising generating a prompt for additional input, based on the conclusion, the prompt included in a rendering of the structured document. 16. The method of claim 14 , further comprising: receiving input representing the content; and maintaining the prompt in the rendering of the structured document.
| 0.898957 |
2. The virtual learning system of claim 1 , further comprising a motion condition generation unit configured to present a predetermined motion condition to the user.
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2. The virtual learning system of claim 1 , further comprising a motion condition generation unit configured to present a predetermined motion condition to the user. 3. The virtual learning system of claim 2 , further comprising an evaluation generation unit communicatively coupled to the computer, wherein the evaluation generation unit is configured to generate an evaluation result that is presented on the display, wherein the evaluation result indicates if the indicator presented on the display was moved correctly according to the predetermined motion condition.
| 0.89302 |
18. The medium of claim 17 , wherein the operations further comprise: determining, based on the probabilistic generative model, that the first node explains the second node; and wherein determining to merge the first node that descends from the one or more parent nodes of the first node with the second node from which the one or more child nodes of the second node descend to generate the combined node comprises: based on determining that the first node explains the second node, determining to merge the first node that descends from the one or more parent nodes of the first node with the second node from which the one or more child nodes of the second node descend to generate the combined node.
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18. The medium of claim 17 , wherein the operations further comprise: determining, based on the probabilistic generative model, that the first node explains the second node; and wherein determining to merge the first node that descends from the one or more parent nodes of the first node with the second node from which the one or more child nodes of the second node descend to generate the combined node comprises: based on determining that the first node explains the second node, determining to merge the first node that descends from the one or more parent nodes of the first node with the second node from which the one or more child nodes of the second node descend to generate the combined node. 19. The medium of claim 18 , wherein the operations further comprise: receiving a set of training documents, wherein each training document contains a set of terms; applying the set of training documents to the probabilistic generative model to produce a new probabilistic generative model; and selecting the new probabilistic generative model as the probabilistic generative model.
| 0.851155 |
1. An apparatus for data processing to perform text and speech analysis of a presentation, the apparatus comprising: a processor coupled to a system bus and operable to access one or more of a serial interface controller and a parallel interface controller, the processor operable to execute instructions to perform a method comprising: obtaining, by the processor, text information corresponding to a presented content, the presented content comprising a plurality of areas, each of the areas comprising a segment of the presented content partitioned according to one or more criteria; performing text analysis, by the processor, on the text information to obtain a first keyword sequence, the first keyword sequence including area keywords associated with at least one area of the plurality of areas; obtaining speech information related to the presented content, the speech information at least comprising a current speech segment of a presenter during a presentation and the speech information is obtained by the processor over the system bus from one or more of the serial interface controller or the parallel interface controller as audio or video of the presenter during the presentation; using a first model network to perform analysis on the current speech segment by the processor to determine the area corresponding to the current speech segment, wherein the first model network comprises the first keyword sequence; obtaining a plurality of second keyword sequences by the processor, at least one of the second keyword sequences corresponding to at least one area of the plurality of areas and at least one of the second keyword sequences comprising at least one keyword; using a second model network to perform analysis on the current speech segment by the processor to determine a keyword corresponding to the current speech segment, the second model network comprising the second keyword sequences; and marking the presented content, by the processor, to attract audience attention based on determining the keyword corresponding to the current speech segment.
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1. An apparatus for data processing to perform text and speech analysis of a presentation, the apparatus comprising: a processor coupled to a system bus and operable to access one or more of a serial interface controller and a parallel interface controller, the processor operable to execute instructions to perform a method comprising: obtaining, by the processor, text information corresponding to a presented content, the presented content comprising a plurality of areas, each of the areas comprising a segment of the presented content partitioned according to one or more criteria; performing text analysis, by the processor, on the text information to obtain a first keyword sequence, the first keyword sequence including area keywords associated with at least one area of the plurality of areas; obtaining speech information related to the presented content, the speech information at least comprising a current speech segment of a presenter during a presentation and the speech information is obtained by the processor over the system bus from one or more of the serial interface controller or the parallel interface controller as audio or video of the presenter during the presentation; using a first model network to perform analysis on the current speech segment by the processor to determine the area corresponding to the current speech segment, wherein the first model network comprises the first keyword sequence; obtaining a plurality of second keyword sequences by the processor, at least one of the second keyword sequences corresponding to at least one area of the plurality of areas and at least one of the second keyword sequences comprising at least one keyword; using a second model network to perform analysis on the current speech segment by the processor to determine a keyword corresponding to the current speech segment, the second model network comprising the second keyword sequences; and marking the presented content, by the processor, to attract audience attention based on determining the keyword corresponding to the current speech segment. 6. The apparatus according to claim 1 , wherein using the second model network to perform analysis on the current speech segment to determine a keyword corresponding to the current speech segment is performed simultaneous with the analysis of the first model network.
| 0.674458 |
2. A method of supporting the proof-reading of a text obtained by speech recognition of a speech signal, of which at least one text component has a reliability level for the correctness of its speech recognition, wherein the method comprises the steps of: control of the progression of the replay speed of the part of the speech signal belonging to the text component as a function of the reliability level of the text component, wherein the progressions of the replay speeds of temporally adjacent parts of the speech signal are adjusted to each other to allow a smooth transition from one component replay speed to another component replay speed.
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2. A method of supporting the proof-reading of a text obtained by speech recognition of a speech signal, of which at least one text component has a reliability level for the correctness of its speech recognition, wherein the method comprises the steps of: control of the progression of the replay speed of the part of the speech signal belonging to the text component as a function of the reliability level of the text component, wherein the progressions of the replay speeds of temporally adjacent parts of the speech signal are adjusted to each other to allow a smooth transition from one component replay speed to another component replay speed. 3. A method as claimed in claim 2 , wherein the progression of the replay speed of the part of the speech signal is controlled without changing the gradient of the pitch of the part of the speech signal.
| 0.639734 |
1. A call processing system comprising: at least one computer processor; and non-transitory memory, which is operably connected to the at least one computer processor, and embodied with a computer program comprising instructions that when executed by the at least one computer processor cause the call processing system to perform operations comprising: receiving a call over a network from a caller directed to a first user device of a user of the call processing system; converting at least a portion of a caller's voice communication associated with the call into a voice communication text; identifying a subset of words in the voice communication text; analyzing at least the content of the identified subset of words of the voice communication text; and promoting to the user of the call processing system, to whom the call was intended, one or more products, services, or products and services via a displayed user interface of an application on a second user device distinct from the first user device to which the received call was directed, based at least in part on the analysis of the content of the identified subset of words of the caller's voice communication text.
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1. A call processing system comprising: at least one computer processor; and non-transitory memory, which is operably connected to the at least one computer processor, and embodied with a computer program comprising instructions that when executed by the at least one computer processor cause the call processing system to perform operations comprising: receiving a call over a network from a caller directed to a first user device of a user of the call processing system; converting at least a portion of a caller's voice communication associated with the call into a voice communication text; identifying a subset of words in the voice communication text; analyzing at least the content of the identified subset of words of the voice communication text; and promoting to the user of the call processing system, to whom the call was intended, one or more products, services, or products and services via a displayed user interface of an application on a second user device distinct from the first user device to which the received call was directed, based at least in part on the analysis of the content of the identified subset of words of the caller's voice communication text. 8. The call processing system as defined in claim 1 , wherein the identification of the subset of words of the voice communication text is based at least in part on one or more keywords and the one or more keywords include activity words.
| 0.882382 |
16. An apparatus comprising: at least one processor; and at least one non-transitory computer-readable storage medium having encoded thereon executable instructions that, when executed by the at least one processor, cause the at least one processor to carry out a method for searching a database of information, the database of information comprising information related to a plurality of content units, the information related to the plurality of content units comprising a plurality of stored annotations related to the plurality of content units by processing the plurality of content units using a first semantic interpretation engine, the first semantic interpretation engine processing the plurality of content units according to at least one annotation model, the method comprising: receiving a query; determining at least one query annotation relating to the query by processing the query using a second semantic interpretation engine, the second semantic interpretation engine processing the query according to the at least one annotation model, wherein the at least one query annotation comprises a first query annotation, wherein the first query annotation comprises a semantic label for the first query annotation and content of the first query annotation; and searching the database based at least in part on the first query annotation wherein the at least one annotation model of the first and second semantic interpretation engines defines at least one annotation type and, for each annotation type of the at least one annotation type, a semantic label for the annotation type and a format of content for the annotation type, wherein the semantic label for an annotation type defined by the at least one annotation model describes a meaning of content of an annotation having the annotation type in context of a content unit from which the content was extracted and that is annotated by the annotation, wherein each stored annotation of the plurality of stored annotations is of an annotation type of the at least one annotation type and annotates a content unit of the plurality of content units, each stored annotation of the plurality of stored annotations comprising the semantic label for the annotation type of the stored annotation and content that was extracted from the content unit that the stored annotation annotates and is of the format defined by the at least one annotation model for content of the annotation type, wherein each query annotation of the at least one query annotation is of an annotation type of the at least one annotation type, each query annotation comprising the semantic label for the annotation type of the query annotation and content that was extracted from the query and is of the format defined by the at least one annotation model for content of the annotation type.
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16. An apparatus comprising: at least one processor; and at least one non-transitory computer-readable storage medium having encoded thereon executable instructions that, when executed by the at least one processor, cause the at least one processor to carry out a method for searching a database of information, the database of information comprising information related to a plurality of content units, the information related to the plurality of content units comprising a plurality of stored annotations related to the plurality of content units by processing the plurality of content units using a first semantic interpretation engine, the first semantic interpretation engine processing the plurality of content units according to at least one annotation model, the method comprising: receiving a query; determining at least one query annotation relating to the query by processing the query using a second semantic interpretation engine, the second semantic interpretation engine processing the query according to the at least one annotation model, wherein the at least one query annotation comprises a first query annotation, wherein the first query annotation comprises a semantic label for the first query annotation and content of the first query annotation; and searching the database based at least in part on the first query annotation wherein the at least one annotation model of the first and second semantic interpretation engines defines at least one annotation type and, for each annotation type of the at least one annotation type, a semantic label for the annotation type and a format of content for the annotation type, wherein the semantic label for an annotation type defined by the at least one annotation model describes a meaning of content of an annotation having the annotation type in context of a content unit from which the content was extracted and that is annotated by the annotation, wherein each stored annotation of the plurality of stored annotations is of an annotation type of the at least one annotation type and annotates a content unit of the plurality of content units, each stored annotation of the plurality of stored annotations comprising the semantic label for the annotation type of the stored annotation and content that was extracted from the content unit that the stored annotation annotates and is of the format defined by the at least one annotation model for content of the annotation type, wherein each query annotation of the at least one query annotation is of an annotation type of the at least one annotation type, each query annotation comprising the semantic label for the annotation type of the query annotation and content that was extracted from the query and is of the format defined by the at least one annotation model for content of the annotation type. 20. The apparatus of claim 16 , wherein: the at least one annotation type defined by the at least one annotation model comprises a plurality of annotation types; the at least one annotation model is adjusted over time to alter the plurality of annotation types defined by the at least one annotation model; at least a portion of the plurality of content units were processed by the first semantic interpretation engine at a first time according to the at least one annotation model, the at least one annotation model defining, at the first time, a first plurality of annotation types; and the determining the at least one query annotation relating to the query by processing the query using the second semantic interpretation engine comprises using, at a second time later than the first time, the second semantic interpretation engine that processes the query according to the at least one annotation model, the at least one annotation model defining, at the second time, a second plurality of annotation types, the second plurality of annotation types defined by the at least one annotation model at the second time being compatible with the first plurality of annotation types defined by the at least one annotation model at the first time.
| 0.500274 |
16. A system for requesting social services from group of users, the system comprises of: a central server unit; at least one service provider and/or searcher computer system providing a service and/or performing a search in response to a service request and/or query from a requestor or searching user; at least one search system receiving request that the group service providers and/or group searching is required, presenting a list of groups of service providers and/or groups of searchers having human service providers and/or searcher members with domain specific expertise and rating, receiving selection of a desired service and/or search groups, prompting for and receiving an authentication information from the requestor or searching user, validating the authentication information, determining whether the requestor or searching user may submit the service request and/or query to a human service provider and/or searcher member of the related or selected service providers group and/or searcher group or a service provider or searcher who is not the human service provider or searcher member based on the match making, connections and subscriptions, and accepting the request or query from the requestor or searching user; a service providers and searchers group database including a service providers and search service of searchers service profiles, service name, ID, service types, service details, service categories, taxonomy, ontology, keywords, ranking, hit statistics, comments, service data including request and response resources, list and profile details of group members; a user system including at least one requestor or searching user interface using which the required service providers or searchers group is selected, the list of service providers or searchers groups being presented in an order based at least in part on the ranking of the service providers or searchers groups; a service providers or searchers of groups database including a service provider or searcher profile(s) including name, location, language, resume, qualification, background, experience, identity data, group identity data, authentication information, user data, ranking hit statistics; and an authorized requestors or searching users or registered subscribers database including the service providers or searchers group identity, an authorized user identity and authentication information, and where at least one of the human service provider or searcher members is selected to provide service or perform the search in response to the request or query from the requester or searching user based on a combination of a categories or keywords of the service or search, two way match making preferences, connections and subscriptions.
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16. A system for requesting social services from group of users, the system comprises of: a central server unit; at least one service provider and/or searcher computer system providing a service and/or performing a search in response to a service request and/or query from a requestor or searching user; at least one search system receiving request that the group service providers and/or group searching is required, presenting a list of groups of service providers and/or groups of searchers having human service providers and/or searcher members with domain specific expertise and rating, receiving selection of a desired service and/or search groups, prompting for and receiving an authentication information from the requestor or searching user, validating the authentication information, determining whether the requestor or searching user may submit the service request and/or query to a human service provider and/or searcher member of the related or selected service providers group and/or searcher group or a service provider or searcher who is not the human service provider or searcher member based on the match making, connections and subscriptions, and accepting the request or query from the requestor or searching user; a service providers and searchers group database including a service providers and search service of searchers service profiles, service name, ID, service types, service details, service categories, taxonomy, ontology, keywords, ranking, hit statistics, comments, service data including request and response resources, list and profile details of group members; a user system including at least one requestor or searching user interface using which the required service providers or searchers group is selected, the list of service providers or searchers groups being presented in an order based at least in part on the ranking of the service providers or searchers groups; a service providers or searchers of groups database including a service provider or searcher profile(s) including name, location, language, resume, qualification, background, experience, identity data, group identity data, authentication information, user data, ranking hit statistics; and an authorized requestors or searching users or registered subscribers database including the service providers or searchers group identity, an authorized user identity and authentication information, and where at least one of the human service provider or searcher members is selected to provide service or perform the search in response to the request or query from the requester or searching user based on a combination of a categories or keywords of the service or search, two way match making preferences, connections and subscriptions. 23. The system as claimed in claim 16 , wherein enabling service providers or searchers of related group to submit one or more service request or queries to one or more selected or matched sources for service request or query specific one or more resources.
| 0.735524 |
1. A non-transitory computer readable medium storing a program which when executed by at least one processing unit identifies an entity having an entity attribute in a document, the program comprising sets of instructions for: receiving, from each process of a plurality of processes, a corresponding set of candidate identity attributes that are each for identifying a particular entity having said entity attribute specified in the document, wherein each process of the plurality of processes generates the corresponding set of candidate identity attributes based on the entity attribute specified in the document; calculating a score for each candidate identity attribute in the sets of candidate identity attributes, the calculating of a score for a particular candidate identity attribute comprising (1) identifying a set of tokens in the particular candidate identity attribute, (2) assigning a value to each token in the set of tokens based on a token count that represents a number of instances of the token across the sets of candidate identity attributes and (3) calculating the score based on the assigned values; and identifying, based on the scores calculated for the candidate identity attributes, an identity attribute from the sets of candidate identity attributes that identifies the entity having said entity attribute specified in the document, wherein a process in the plurality of processes comprises a service that identifies the set of candidate identity attributes based on a probability of a set of keywords appearing in the document.
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1. A non-transitory computer readable medium storing a program which when executed by at least one processing unit identifies an entity having an entity attribute in a document, the program comprising sets of instructions for: receiving, from each process of a plurality of processes, a corresponding set of candidate identity attributes that are each for identifying a particular entity having said entity attribute specified in the document, wherein each process of the plurality of processes generates the corresponding set of candidate identity attributes based on the entity attribute specified in the document; calculating a score for each candidate identity attribute in the sets of candidate identity attributes, the calculating of a score for a particular candidate identity attribute comprising (1) identifying a set of tokens in the particular candidate identity attribute, (2) assigning a value to each token in the set of tokens based on a token count that represents a number of instances of the token across the sets of candidate identity attributes and (3) calculating the score based on the assigned values; and identifying, based on the scores calculated for the candidate identity attributes, an identity attribute from the sets of candidate identity attributes that identifies the entity having said entity attribute specified in the document, wherein a process in the plurality of processes comprises a service that identifies the set of candidate identity attributes based on a probability of a set of keywords appearing in the document. 11. The non-transitory computer readable medium of claim 1 , wherein the process in the plurality of processes is a first process, wherein a second process in the plurality of processes generates a set of candidate identity attributes by a query to an entity database.
| 0.667169 |
1. A processor-implemented method for identifying domain-specific concepts in multiple subdiscussions in an online discussion using concept commonality measures by identifying features including relevance within the online discussion to generate inferences, the online discussion being stored in a memory communicatively coupled to a processor, the processor executing the concept commonality measures to perform the processor-implemented method, the processor-implemented method comprising: identifying, by the processor, a first concept relevant to a first subdiscussion associated with the online discussion; identifying, by the processor, a second concept relevant to the first subdiscussion; determining, by the processor, a first relation between the first concept and the second concept; computing, by the processor, a first relevance that corresponds to the first concept and the first subdiscussion based on a number of other subdiscussions associated with the first concept and a frequency associated with the first concept and the first subdiscussion, wherein the concept commonality measures comprise the first relevance, wherein the concept commonality measures support the inferences in the online discussion; displaying, via a display communicatively coupled to the processor and the memory, a user interface comprising the first relevance, identifying a first participant associated with a first text segment corresponding to the online discussion; identifying a second participant associated with a second text segment corresponding to the online discussion; and determining a second relation between the first participant and the second participant based at least in part on one selected from a response matrix and a content matrix, wherein the response matrix corresponds to a first participation in the online discussion by the first participant and a second participation in the online discussion by the second participant, and wherein the content matrix corresponds to a comparison of the first text segment and the second text segment.
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1. A processor-implemented method for identifying domain-specific concepts in multiple subdiscussions in an online discussion using concept commonality measures by identifying features including relevance within the online discussion to generate inferences, the online discussion being stored in a memory communicatively coupled to a processor, the processor executing the concept commonality measures to perform the processor-implemented method, the processor-implemented method comprising: identifying, by the processor, a first concept relevant to a first subdiscussion associated with the online discussion; identifying, by the processor, a second concept relevant to the first subdiscussion; determining, by the processor, a first relation between the first concept and the second concept; computing, by the processor, a first relevance that corresponds to the first concept and the first subdiscussion based on a number of other subdiscussions associated with the first concept and a frequency associated with the first concept and the first subdiscussion, wherein the concept commonality measures comprise the first relevance, wherein the concept commonality measures support the inferences in the online discussion; displaying, via a display communicatively coupled to the processor and the memory, a user interface comprising the first relevance, identifying a first participant associated with a first text segment corresponding to the online discussion; identifying a second participant associated with a second text segment corresponding to the online discussion; and determining a second relation between the first participant and the second participant based at least in part on one selected from a response matrix and a content matrix, wherein the response matrix corresponds to a first participation in the online discussion by the first participant and a second participation in the online discussion by the second participant, and wherein the content matrix corresponds to a comparison of the first text segment and the second text segment. 4. The processor-implemented method of claim 1 , further comprising: computing a second relevance corresponding to the second concept and the first subdiscussion; and ranking the second concept relative to the first concept based at least in part on the first relevance and the second relevance.
| 0.535843 |
1. A method for providing access to information using personalized search engines, comprising: identifying a multiplicity of personalized search engines, wherein each personalized search engine performs searches using at least two base search engines, and wherein one or more of the personalized search engines include different combinations of base search engines; obtaining characteristic information for each personalized search engine, wherein characteristic information for a personalized search engine includes one or more characteristic keywords representing searching capabilities of said personalized search engine; and dynamically selecting a personalized search engine among the multiple personalized search engines for executing a query based on characteristic information for each personalized search engine and the query; wherein characteristic information for the selected personalized search engine is updated based on one or more keywords extracted from search results returned by the selected personalized search engine; and wherein dynamically selecting a personalized search engine comprises: for each personalized search engine, determining a similarity between one or more user entered query keywords and characteristic information for the personalized search engine; and selecting a personalized search engine based on each similarity determined.
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1. A method for providing access to information using personalized search engines, comprising: identifying a multiplicity of personalized search engines, wherein each personalized search engine performs searches using at least two base search engines, and wherein one or more of the personalized search engines include different combinations of base search engines; obtaining characteristic information for each personalized search engine, wherein characteristic information for a personalized search engine includes one or more characteristic keywords representing searching capabilities of said personalized search engine; and dynamically selecting a personalized search engine among the multiple personalized search engines for executing a query based on characteristic information for each personalized search engine and the query; wherein characteristic information for the selected personalized search engine is updated based on one or more keywords extracted from search results returned by the selected personalized search engine; and wherein dynamically selecting a personalized search engine comprises: for each personalized search engine, determining a similarity between one or more user entered query keywords and characteristic information for the personalized search engine; and selecting a personalized search engine based on each similarity determined. 6. The method of claim 1 , further comprising: causing execution of the query on the selected personalized search engine; obtaining search results retrieved by the selected personalized search engine upon execution of the query; analyzing quality of the search results based on one or more of the query and characteristic information for the selected personalized search engine; and scoring the selected personalized search engine based on the quality of the search results.
| 0.63182 |
1. A method performed by a user computer upon loading a web page of a web site, said web page including an update handler tag, the method comprising: at least partly in response to the update handler tag, loading an update handler over a network, said update handler comprising browser-executable code that is loaded as part of the web page by a browser running on the user computer; and via execution of the update handler by said browser running on the user computer: (a) detecting, via an analysis of content of the web page, a reference in the web page to a product represented in an electronic catalog of products, said reference comprising a product identifier included in a link that points to a catalog page associated with the product, wherein detecting the reference comprises determining whether the link matches a pre-specified link signature of a catalog page; (b) retrieving, over a network from a content server that is separate from the web site, supplemental content, including catalog content, associated with the product; and (c) in response to a mouse-over event involving the product, causing the user computer to display the supplemental content in an overlay display object added to the web page.
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1. A method performed by a user computer upon loading a web page of a web site, said web page including an update handler tag, the method comprising: at least partly in response to the update handler tag, loading an update handler over a network, said update handler comprising browser-executable code that is loaded as part of the web page by a browser running on the user computer; and via execution of the update handler by said browser running on the user computer: (a) detecting, via an analysis of content of the web page, a reference in the web page to a product represented in an electronic catalog of products, said reference comprising a product identifier included in a link that points to a catalog page associated with the product, wherein detecting the reference comprises determining whether the link matches a pre-specified link signature of a catalog page; (b) retrieving, over a network from a content server that is separate from the web site, supplemental content, including catalog content, associated with the product; and (c) in response to a mouse-over event involving the product, causing the user computer to display the supplemental content in an overlay display object added to the web page. 7. The method of claim 1 , wherein the step of detecting the reference to the product via an analysis of content of the web page occurs in response to the mouse-over event.
| 0.560934 |
1. A handheld motion control system comprising: a motion detector within a handheld motion device, the motion detector having a three-axis acceleration sensor; a device locator within the handheld motion device, the device locator configured to: receive motion information obtained by the motion detector within the handheld motion device, wherein the motion information comprises a set of points traversed by the handheld motion device between a starting point base reference position and a stopping point; identify and select a device to be controlled from among a plurality of devices based on the motion information and device selection information, the device selection information correlating different motion information with different devices of the plurality of devices; and wherein the starting point base reference position is associated with an orientation of the handheld motion device relative to the device identified and selected to be controlled; a wireless communication interface configured to communicate device commands for the selected device, the device commands communicated from the handheld motion device to a processing apparatus of the selected device configured to obtain the information from the wireless communication interface to process the device commands; and wherein the motion detector is operable to allow a user to reset the starting point base reference position of the handheld motion device.
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1. A handheld motion control system comprising: a motion detector within a handheld motion device, the motion detector having a three-axis acceleration sensor; a device locator within the handheld motion device, the device locator configured to: receive motion information obtained by the motion detector within the handheld motion device, wherein the motion information comprises a set of points traversed by the handheld motion device between a starting point base reference position and a stopping point; identify and select a device to be controlled from among a plurality of devices based on the motion information and device selection information, the device selection information correlating different motion information with different devices of the plurality of devices; and wherein the starting point base reference position is associated with an orientation of the handheld motion device relative to the device identified and selected to be controlled; a wireless communication interface configured to communicate device commands for the selected device, the device commands communicated from the handheld motion device to a processing apparatus of the selected device configured to obtain the information from the wireless communication interface to process the device commands; and wherein the motion detector is operable to allow a user to reset the starting point base reference position of the handheld motion device. 8. The motion control system according to claim 1 , wherein the motion detector of the handheld device includes a processor operable to allow a user to repeatedly selectively engage and disengage motion sensitivity.
| 0.510903 |
48. A tangible, non-transitory, computer-readable storage medium storing computer-readable instructions for causing data processing apparatus to perform certain operations to generate module data for use with a personalized container document, the instructions comprising: identifying particular code that corresponds to a first module, the first module selectively designated for inclusion in a personalized container document, wherein the particular code provides first module data and parameters associated with the first module, wherein the first module data is adapted for use in the personalized container document, the parameters of the particular code including a first content element and one or more preference elements; identifying additional code that corresponds to a second module selectively designated for inclusion in the personalized container document, wherein the additional code provides second module data and parameters associated with the second module, wherein the second module data is adapted for use in the personalized container document, the parameters of the additional code including a second content element; receiving, into memory, the first module data and the second module data; serving the first module data and the second module data with the personalized container document to a remote browser client; wherein the personalized container document defines an organization for a presentation of content associated with the first module and the second module in a container document display, wherein for each module a portion of the container document display is allocated for the presentation of content corresponding to the module; wherein the first module data and the second module data includes computer-executable instructions adapted for execution by the remote browser client to render content for the corresponding module for presentation in the container document display; and wherein the first content element is different than the second content element and the one or more preference elements include at least one module preference element adapted to specify at least two alternative presentation states of content for the first module, the at least one module preference element defining conditions that change independent of user input in the container document display for dynamically presenting content in one of the at least two presentation states, with content rendered, using the computer-executable instructions executed by the remote browser client, in a first of the at least two presentation states in response to a first condition and rendered, using the computer-executable instructions executed by the remote browser client, in a second of the at least two presentation states in response to a second condition.
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48. A tangible, non-transitory, computer-readable storage medium storing computer-readable instructions for causing data processing apparatus to perform certain operations to generate module data for use with a personalized container document, the instructions comprising: identifying particular code that corresponds to a first module, the first module selectively designated for inclusion in a personalized container document, wherein the particular code provides first module data and parameters associated with the first module, wherein the first module data is adapted for use in the personalized container document, the parameters of the particular code including a first content element and one or more preference elements; identifying additional code that corresponds to a second module selectively designated for inclusion in the personalized container document, wherein the additional code provides second module data and parameters associated with the second module, wherein the second module data is adapted for use in the personalized container document, the parameters of the additional code including a second content element; receiving, into memory, the first module data and the second module data; serving the first module data and the second module data with the personalized container document to a remote browser client; wherein the personalized container document defines an organization for a presentation of content associated with the first module and the second module in a container document display, wherein for each module a portion of the container document display is allocated for the presentation of content corresponding to the module; wherein the first module data and the second module data includes computer-executable instructions adapted for execution by the remote browser client to render content for the corresponding module for presentation in the container document display; and wherein the first content element is different than the second content element and the one or more preference elements include at least one module preference element adapted to specify at least two alternative presentation states of content for the first module, the at least one module preference element defining conditions that change independent of user input in the container document display for dynamically presenting content in one of the at least two presentation states, with content rendered, using the computer-executable instructions executed by the remote browser client, in a first of the at least two presentation states in response to a first condition and rendered, using the computer-executable instructions executed by the remote browser client, in a second of the at least two presentation states in response to a second condition. 49. The computer-readable storage medium of claim 48 wherein one or more preferences comprise user preferences.
| 0.500719 |
2. The computer program product in accordance with claim 1 , wherein when the language service provider port component holds a plurality of language service providers, the management component is further configured to select one of the plurality of language service providers to provide the set of available symbols.
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2. The computer program product in accordance with claim 1 , wherein when the language service provider port component holds a plurality of language service providers, the management component is further configured to select one of the plurality of language service providers to provide the set of available symbols. 6. The computer program product in accordance with claim 2 , wherein the management component is further configured to disable a language service provider of the plurality of language service providers if a performance of the language service provider crashes or otherwise has poor performance.
| 0.859608 |
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