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4. The method of claim 3 , wherein the code of the second template contains a default value for one of the one or more variables defined within the code of the second template.
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4. The method of claim 3 , wherein the code of the second template contains a default value for one of the one or more variables defined within the code of the second template. 6. The method of claim 4 , further comprising presenting to a user of the SOA composite editor the code for the definition of the service including the inserted updated code of the first template and the inserted code of the second template.
| 0.953136 |
1. One or more computer storage media including computer executable instructions embodied thereon that, when executed by one or more computing devices, cause the one or more computing devices to perform a method for generating instructions for filling a predetermined region, the method comprising: receiving a dithered specification for the predetermined region; generating a lattice corresponding to the dithered specification, wherein the lattice is populated with a set of vertices, a set of edges connecting the vertices, and cost function data associated with the edges on-the-fly; recursively performing an overlapping divide-and-conquer beam search on the lattice to determine a path through a subset of vertices included in the lattice that minimizes an overall cost of filling the predetermined region, wherein the overall cost is calculated from the cost function data associated with the edges that connect the subset of vertices; and outputting instructions to a processor for the placement of building blocks in the predetermined region, the instructions generated using the determined path.
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1. One or more computer storage media including computer executable instructions embodied thereon that, when executed by one or more computing devices, cause the one or more computing devices to perform a method for generating instructions for filling a predetermined region, the method comprising: receiving a dithered specification for the predetermined region; generating a lattice corresponding to the dithered specification, wherein the lattice is populated with a set of vertices, a set of edges connecting the vertices, and cost function data associated with the edges on-the-fly; recursively performing an overlapping divide-and-conquer beam search on the lattice to determine a path through a subset of vertices included in the lattice that minimizes an overall cost of filling the predetermined region, wherein the overall cost is calculated from the cost function data associated with the edges that connect the subset of vertices; and outputting instructions to a processor for the placement of building blocks in the predetermined region, the instructions generated using the determined path. 3. The one or more computer storage media of claim 1 , wherein the method further comprises generating the lattice such that each vertex represents a particular arrangement of building blocks.
| 0.54563 |
82. The computer program product of claim 29 , wherein the computer program product is configured for identifying taxonomy software elements in connection with at least one source data document.
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82. The computer program product of claim 29 , wherein the computer program product is configured for identifying taxonomy software elements in connection with at least one source data document. 90. The computer program product of claim 82 , wherein the computer program product is configured such that at least one of: at least one of said taxonomy software elements includes a Numerator Document Object Model; said taxonomy software elements include at least one attribute; said taxonomy software elements include a level attribute; said taxonomy software elements reflect the multiple hierarchical relationships by representing corresponding elements of an eXtensible Business Reporting Language (XBRL) taxonomy document; said taxonomy software elements reflect the multiple hierarchical relationships by having a format associated with the hierarchal relationships; or said at least one computer-readable semantic tag includes at least one of a schema tag, an annotation tag, an element tag, a documentation tag, an appinfo tag, a rollup tag, a label tag, a reference tag, or an XBLR tag.
| 0.919223 |
12. A non-transitory computer-readable medium comprising instructions to cause a computing device, in response to execution of the instructions, to: receive a plurality of facial motion parameters and a plurality of head gestures parameters, respectively associated with a face and a head of a user; and drive an avatar model with facial and skeleton animations to animate the avatar, employing at least a head bone and a torso bone connected at a joint and using the facial motion parameters and the head gestures parameters to replicate a facial expression of the user on the avatar, that includes impact of head post rotation of the user; wherein the plurality of facial motion parameters depict facial action movements of the face, and the plurality of head gestures parameters depict head pose gestures of the head; wherein to drive comprises application of head rotation impact weights while driving the avatar model with facial and skeleton animations; and wherein application comprises application of head rotation impact weights from a head rotation impact weight map pre-generated employing the at least a head bone and a torso bone connected at a joint.
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12. A non-transitory computer-readable medium comprising instructions to cause a computing device, in response to execution of the instructions, to: receive a plurality of facial motion parameters and a plurality of head gestures parameters, respectively associated with a face and a head of a user; and drive an avatar model with facial and skeleton animations to animate the avatar, employing at least a head bone and a torso bone connected at a joint and using the facial motion parameters and the head gestures parameters to replicate a facial expression of the user on the avatar, that includes impact of head post rotation of the user; wherein the plurality of facial motion parameters depict facial action movements of the face, and the plurality of head gestures parameters depict head pose gestures of the head; wherein to drive comprises application of head rotation impact weights while driving the avatar model with facial and skeleton animations; and wherein application comprises application of head rotation impact weights from a head rotation impact weight map pre-generated employing the at least a head bone and a torso bone connected at a joint. 15. The computer-readable medium of claim 12 , wherein the head rotation impact weight map has a layout that includes a section for the face, a section for eyeballs of the face, a section for a neck of the user, a section for a tongue of the face, a section for teeth of the face or a section for a body or clothing of the user.
| 0.623262 |
1. A non-transitory computer-readable medium having a plurality of instructions executable by a first computing device stored thereon, the plurality of instructions, when executed by the first computing device, causing the first computing device to at least: obtain a foreign language search query associated with a search request comprising at least one search term; detect a language associated with the foreign language search query; determine that the language associated with the foreign language search query differs from an expected language; identify a foreign language page template associated with the language; and in response to determining that the language differs, generate a search result user interface for display, the search result user interface including at least one alternative search result based at least in part on the foreign language template corresponding to the language.
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1. A non-transitory computer-readable medium having a plurality of instructions executable by a first computing device stored thereon, the plurality of instructions, when executed by the first computing device, causing the first computing device to at least: obtain a foreign language search query associated with a search request comprising at least one search term; detect a language associated with the foreign language search query; determine that the language associated with the foreign language search query differs from an expected language; identify a foreign language page template associated with the language; and in response to determining that the language differs, generate a search result user interface for display, the search result user interface including at least one alternative search result based at least in part on the foreign language template corresponding to the language. 5. The non-transitory computer-readable medium of claim 1 , wherein the foreign language page template comprises at least one of a string or an image varying in size from an expected language page template.
| 0.640337 |
2. The method of claim 1 , comprising constraining W to be a plurality of sparse matrix zero entries for pairs of words irrelevant to the preference learning.
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2. The method of claim 1 , comprising constraining W to be a plurality of sparse matrix zero entries for pairs of words irrelevant to the preference learning. 3. The method of claim 2 , comprising imposing an entry-wise l 1 regularization on W.
| 0.972436 |
29. The system of claim 18 , wherein the collection of content items is presented on the user device, the user device being a hand-held device.
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29. The system of claim 18 , wherein the collection of content items is presented on the user device, the user device being a hand-held device. 30. The system of claim 29 , wherein the hand-held device is at least one of a telephone, a PDA, and a remote control.
| 0.961868 |
17. The method of claim 15 , wherein the method further comprises determining one or more search results based on the search query.
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17. The method of claim 15 , wherein the method further comprises determining one or more search results based on the search query. 18. The method of claim 17 , wherein the method further comprises communicating at least a portion of the one or more search results for presentation to the end user.
| 0.921277 |
5. The token stitcher of claim 4 , wherein the token stitcher engine is configured to identify which programs are associated with the new token received over the input line by performing: upon the token stitcher engine identifying which flags in the flag bank are asserted, the token stitcher engine consulting a hash table to determine if any of a set of keys are mapped, by the hash table, to associated values. wherein each key in the set of keys is associated with a different asserted flag in the flag bank.
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5. The token stitcher of claim 4 , wherein the token stitcher engine is configured to identify which programs are associated with the new token received over the input line by performing: upon the token stitcher engine identifying which flags in the flag bank are asserted, the token stitcher engine consulting a hash table to determine if any of a set of keys are mapped, by the hash table, to associated values. wherein each key in the set of keys is associated with a different asserted flag in the flag bank. 8. The token stitcher of claim 5 , wherein the token stitcher engine consulting a hash table comprises: the token stitcher engine consulting the hash table to determine if a first key is mapped by the hash table to a first associated value that identifies or corresponds to a first program; the token stitcher engine causing the first program to be executed; and after the first program is executed, the token stitcher engine consulting the hash table to determine if a second key is mapped by the hash table, to a second associated value that identifies or corresponds to a second program.
| 0.738787 |
8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by a mobile device that includes a camera and a display, data identifying a selected image acquisition template associated with a particular type of object, from among multiple image acquisition templates that are stored on the multiple device and that are each associated with a different type of object; providing a pattern associated with the selected image acquisition template for output on the display; generating, by the camera included on the mobile device, a query image while the pattern associated with the selected image acquisition template is provided for output on the display; providing, to a search engine, an image search query that includes (i) the query image, and (ii) an indication of the selected image acquisition template; and receiving, from the search engine, one or more image search results in response to the image search query.
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8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by a mobile device that includes a camera and a display, data identifying a selected image acquisition template associated with a particular type of object, from among multiple image acquisition templates that are stored on the multiple device and that are each associated with a different type of object; providing a pattern associated with the selected image acquisition template for output on the display; generating, by the camera included on the mobile device, a query image while the pattern associated with the selected image acquisition template is provided for output on the display; providing, to a search engine, an image search query that includes (i) the query image, and (ii) an indication of the selected image acquisition template; and receiving, from the search engine, one or more image search results in response to the image search query. 9. The system of claim 8 , wherein receiving the data identifying the selected image acquisition template is based on at least one of a selection by a user and automatic selection of the selected image acquisition template by the mobile device based on identifying a general category of the particular type of the object.
| 0.535228 |
1. A method of allowing a user to control a mobile communication facility comprising: receiving speech and information currently displayed in a mobile communication facility from a user using a mobile communication facility resident capture facility, wherein the speech presented by the user includes a command and a subject and wherein the speech and information was transmitted from the mobile communication facility to a speech recognition facility; utilizing, by the speech recognition facility, (i) contextual information not provided in the speech and (ii) at least one statistical language model to recognize the command and a subject from the speech presented by the user, wherein the contextual information includes usage history of the mobile communication facility, information from a user's favorites list, information about the user's address book or contact list, email content, or information currently displayed in by the mobile communication facility; determining, by the speech recognition facility, at least one application to invoke on the mobile communication facility to perform an operation on the mobile communication facility based on the contextual information, the command, and the subject of the speech, wherein the operation includes an action defined by the command using parameters based on the subject; and causing the mobile communication facility to automatically perform the operation on the mobile communication facility using the determined at least one application.
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1. A method of allowing a user to control a mobile communication facility comprising: receiving speech and information currently displayed in a mobile communication facility from a user using a mobile communication facility resident capture facility, wherein the speech presented by the user includes a command and a subject and wherein the speech and information was transmitted from the mobile communication facility to a speech recognition facility; utilizing, by the speech recognition facility, (i) contextual information not provided in the speech and (ii) at least one statistical language model to recognize the command and a subject from the speech presented by the user, wherein the contextual information includes usage history of the mobile communication facility, information from a user's favorites list, information about the user's address book or contact list, email content, or information currently displayed in by the mobile communication facility; determining, by the speech recognition facility, at least one application to invoke on the mobile communication facility to perform an operation on the mobile communication facility based on the contextual information, the command, and the subject of the speech, wherein the operation includes an action defined by the command using parameters based on the subject; and causing the mobile communication facility to automatically perform the operation on the mobile communication facility using the determined at least one application. 2. The method of claim 1 further comprising deciding whether the at least one statistical language model provides insufficient recognition output and selecting at least one other language model apart from the set of language models based on speech recognized by the selected at least one statistical language model.
| 0.597781 |
36. The non-transitory computer storage medium of claim 27 , wherein the operations further comprise: receiving input from a second user indicating that one or more of the first documents are preferred documents; calculating a respective document weight for each of the preferred documents; nd wherein calculating the aggregate strength of relationship score for each candidate document includes weighting the strength of relationship scores for the candidate document and each of the preferred documents by the respective document weight for the preferred document.
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36. The non-transitory computer storage medium of claim 27 , wherein the operations further comprise: receiving input from a second user indicating that one or more of the first documents are preferred documents; calculating a respective document weight for each of the preferred documents; nd wherein calculating the aggregate strength of relationship score for each candidate document includes weighting the strength of relationship scores for the candidate document and each of the preferred documents by the respective document weight for the preferred document. 38. The non-transitory computer storage medium of claim 36 , wherein the operations further comprise presenting one or more of the second documents as suggested documents.
| 0.839681 |
1. A computerized method for substantially eliminating financial account fraud or theft, said method including the utilization of electronic communication devices by a financial institution, a financial account holder, and, optionally, a third party, said method involving an intermediary algorithm system that a) stores within a database profile information pertaining to said financial institution, said financial account holder, and said optional third party as searchable data, b) generates searches of said searchable data upon request of verification of financial account holder identity by said financial institution in relation to a financial transaction, wherein the results of said searches are provided as unique string variables, c) communicates with profile contact points meeting all criteria defined within said search results, and d) verifies contact point identity in relation to said search criteria and said profile information, said method comprising the steps of: 1) initiating a protocol between said financial institution and said financial account holder through said intermediary algorithm system in relation to a financial account held by said financial account holder and serviced by said financial institution, wherein said protocol initiation comprises a) generating at least one financial account holder profile and a financial institution profile within said intermediary algorithm system, said financial account holder profile and said financial institution profile both comprising a client identifier relating to the identity of said financial account holder and verification contact point requirements to be undertaken by said intermediary algorithm system upon utilization of said financial account within a transaction; 2) establishing specific contact point identifications within said intermediary algorithm system through communicating with each required verification contact point within both profiles of said financial account holder and said financial institution; 3) initiating a financial transaction by said financial account holder to transfer funds to or from said financial institution in relation to said financial account holder's account; 4) requesting verification of the identity of said financial account holder by said financial institution through communicating with said intermediary algorithm system prior to completion of said financial transaction; 5) upon receipt of such a request, generating by said intermediary algorithm system search criteria including identifiers related to said requested financial transaction; 6) upon generation of said search criteria, said intermediary algorithm system creating said unique string of variables based upon results of said search criteria, said string including contact point requirements associated with said financial account holder of said financial transaction; 7) said intermediary algorithm system retaining said unique string of variables in order to a) validate profile identities associated with said financial transaction, b) identify all matching profiles meeting said search criteria, and c) identify the search associated with said search criteria; 8) transmitting a request for response from said intermediary algorithm system to each contact point associated with said at least one account holder profile, wherein said request includes said unique string of variables and a request for return of said string variables from each contact point; 9) holding said transaction open by said intermediary algorithm system until verification of said financial account holder identity is completed; 10) receiving at least one response from each contact point by said intermediary algorithm system; 11) confirming the presence of said unique string of variables within said at least one received response by said intermediary algorithm system; 12) confirming the match of each contact point from which said response is received with at least one contact point within said database by said intermediary algorithm system; 13) confirming the match of said account holder profile in comparison with said search criteria of step “5” by said intermediary algorithm system; 14) authorizing said transaction by said intermediary algorithm system if each of steps “11,” “12,” and “13” are confirmed, wherein if any of said steps “11,” “12,” or “13” are not confirmed, then said intermediary algorithm system invalidates said financial account holder identity and prohibits said transaction from proceeding; and 15) transferring the result of step “14” from said intermediary algorithm system to each of said financial account holder, said financial institution, and said optional third party; wherein said method is undertaken through the utilization of at least one computer program within a non-transitory medium.
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1. A computerized method for substantially eliminating financial account fraud or theft, said method including the utilization of electronic communication devices by a financial institution, a financial account holder, and, optionally, a third party, said method involving an intermediary algorithm system that a) stores within a database profile information pertaining to said financial institution, said financial account holder, and said optional third party as searchable data, b) generates searches of said searchable data upon request of verification of financial account holder identity by said financial institution in relation to a financial transaction, wherein the results of said searches are provided as unique string variables, c) communicates with profile contact points meeting all criteria defined within said search results, and d) verifies contact point identity in relation to said search criteria and said profile information, said method comprising the steps of: 1) initiating a protocol between said financial institution and said financial account holder through said intermediary algorithm system in relation to a financial account held by said financial account holder and serviced by said financial institution, wherein said protocol initiation comprises a) generating at least one financial account holder profile and a financial institution profile within said intermediary algorithm system, said financial account holder profile and said financial institution profile both comprising a client identifier relating to the identity of said financial account holder and verification contact point requirements to be undertaken by said intermediary algorithm system upon utilization of said financial account within a transaction; 2) establishing specific contact point identifications within said intermediary algorithm system through communicating with each required verification contact point within both profiles of said financial account holder and said financial institution; 3) initiating a financial transaction by said financial account holder to transfer funds to or from said financial institution in relation to said financial account holder's account; 4) requesting verification of the identity of said financial account holder by said financial institution through communicating with said intermediary algorithm system prior to completion of said financial transaction; 5) upon receipt of such a request, generating by said intermediary algorithm system search criteria including identifiers related to said requested financial transaction; 6) upon generation of said search criteria, said intermediary algorithm system creating said unique string of variables based upon results of said search criteria, said string including contact point requirements associated with said financial account holder of said financial transaction; 7) said intermediary algorithm system retaining said unique string of variables in order to a) validate profile identities associated with said financial transaction, b) identify all matching profiles meeting said search criteria, and c) identify the search associated with said search criteria; 8) transmitting a request for response from said intermediary algorithm system to each contact point associated with said at least one account holder profile, wherein said request includes said unique string of variables and a request for return of said string variables from each contact point; 9) holding said transaction open by said intermediary algorithm system until verification of said financial account holder identity is completed; 10) receiving at least one response from each contact point by said intermediary algorithm system; 11) confirming the presence of said unique string of variables within said at least one received response by said intermediary algorithm system; 12) confirming the match of each contact point from which said response is received with at least one contact point within said database by said intermediary algorithm system; 13) confirming the match of said account holder profile in comparison with said search criteria of step “5” by said intermediary algorithm system; 14) authorizing said transaction by said intermediary algorithm system if each of steps “11,” “12,” and “13” are confirmed, wherein if any of said steps “11,” “12,” or “13” are not confirmed, then said intermediary algorithm system invalidates said financial account holder identity and prohibits said transaction from proceeding; and 15) transferring the result of step “14” from said intermediary algorithm system to each of said financial account holder, said financial institution, and said optional third party; wherein said method is undertaken through the utilization of at least one computer program within a non-transitory medium. 7. The method of claim 1 wherein said optional third party is present therein and wherein step “3” involves a transaction including said third party to transfer financial account holder account funds from said financial institution to said third party.
| 0.523217 |
1. A method for translating a sentence entered by a user into machine recognizable thought patterns, said method comprising: receiving the sentence entered by the user; translating the user's sentence to a universal language; parsing the translated sentence; deriving propositions from the parsed translated sentence of the user; sequentially storing the derived propositions into a knowledge database; and, generating a set of peripheral database linkages for the sets of derived propositions representing the user's sentence, wherein each peripheral database linkage includes a peripheral database representing a function of speech selectively linked to one or more of the other peripheral databases and the knowledge database.
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1. A method for translating a sentence entered by a user into machine recognizable thought patterns, said method comprising: receiving the sentence entered by the user; translating the user's sentence to a universal language; parsing the translated sentence; deriving propositions from the parsed translated sentence of the user; sequentially storing the derived propositions into a knowledge database; and, generating a set of peripheral database linkages for the sets of derived propositions representing the user's sentence, wherein each peripheral database linkage includes a peripheral database representing a function of speech selectively linked to one or more of the other peripheral databases and the knowledge database. 4. A method as claimed in claim 1, further comprising the steps of storing each noun present in each derived proposition into a noun database listing in conjunction with the identification of the proposition the noun first appears respective to the sequential order of the propositions stored in the knowledge database.
| 0.647013 |
1. One or more non-transitory computer-readable medium comprising computer-executable instruction that, when executed by one or more processors, cause the one or more processors to at least: in response to receiving electronic content to be delivered to a destination address, identify a first word in the electronic content and a second word in the electronic content; determine a first base language semantic vector of the first word; determine a second base language semantic vector of the second word; determine, for a keyword, a key word base language semantic vector, the keyword being a taboo word; determine a first distance between the first base language semantic vector and the key word base language semantic vector; determine a second distance between the second base language semantic vector and the key word base language semantic vector; determine that the first distance is less than a threshold distance; determine that the second distance is less than the threshold distance; determine a sum of the first distance and the second distance; determine a score of the electronic content based at least in part on the sum, wherein the score indicates a relevance of the electronic content to the key word; determine that the electronic content is not to be delivered to the destination address based at least in part on the score of the electronic content; and prevent the electronic content from being delivered to the destination address.
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1. One or more non-transitory computer-readable medium comprising computer-executable instruction that, when executed by one or more processors, cause the one or more processors to at least: in response to receiving electronic content to be delivered to a destination address, identify a first word in the electronic content and a second word in the electronic content; determine a first base language semantic vector of the first word; determine a second base language semantic vector of the second word; determine, for a keyword, a key word base language semantic vector, the keyword being a taboo word; determine a first distance between the first base language semantic vector and the key word base language semantic vector; determine a second distance between the second base language semantic vector and the key word base language semantic vector; determine that the first distance is less than a threshold distance; determine that the second distance is less than the threshold distance; determine a sum of the first distance and the second distance; determine a score of the electronic content based at least in part on the sum, wherein the score indicates a relevance of the electronic content to the key word; determine that the electronic content is not to be delivered to the destination address based at least in part on the score of the electronic content; and prevent the electronic content from being delivered to the destination address. 3. The one or more non-transitory computer-readable medium of claim 1 , wherein the determining of the first base language semantic vector includes: determining a native language semantic vector corresponding to the first word; and transforming, based at least in part on a native language-to-base language translation matrix, the native language semantic vector to the first base language semantic vector.
| 0.862963 |
26. The computer program product of claim 25 , wherein the training set of interest is directed to chemical terms.
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26. The computer program product of claim 25 , wherein the training set of interest is directed to chemical terms. 27. The computer program product of claim 26 , further comprising code for annotating the document in view of the identified tokens.
| 0.922468 |
7. Audiometer according to claim 5 further including a data bus (20) connected to said means (21) for generating the electrical signals; a driver circuit (24) connected to the data bus and providing driving power to the LCD in matrix form (11,26); and wherein a data input stage (12) is provided, connected to said data bus and receiving the amplitude control output signal, the test control output signal and the perception output signal, and connecting, respectively, said signals to the driver circuit to energize the LCD in matric form in accordance with said signals.
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7. Audiometer according to claim 5 further including a data bus (20) connected to said means (21) for generating the electrical signals; a driver circuit (24) connected to the data bus and providing driving power to the LCD in matrix form (11,26); and wherein a data input stage (12) is provided, connected to said data bus and receiving the amplitude control output signal, the test control output signal and the perception output signal, and connecting, respectively, said signals to the driver circuit to energize the LCD in matric form in accordance with said signals. 8. Audiometer according to claim 7 further including an output control unit (43) connected to said data bus and providing output signals for an external recording apparatus.
| 0.886912 |
13. The method of claim 12 , further comprising: identifying one or more parameters associated with the task based on a portion of the audio output; wherein performing the task includes performing the task based on the identified one or more parameters.
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13. The method of claim 12 , further comprising: identifying one or more parameters associated with the task based on a portion of the audio output; wherein performing the task includes performing the task based on the identified one or more parameters. 14. The method of claim 13 , further comprising: in response to receipt of the natural language speech input, identifying the portion of the audio output.
| 0.91322 |
26. The computer readable medium of claim 25 , wherein the acts of: detecting includes an act of detecting a plurality of candidate formants; and grouping the plurality of candidate features includes an act of grouping the plurality of candidate features into the plurality of candidate feature sets for each of the plurality of frames such that each of the plurality of candidate feature sets includes at least one value representative of each of a first formant, a second formant and a third formant detected in the respective frame.
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26. The computer readable medium of claim 25 , wherein the acts of: detecting includes an act of detecting a plurality of candidate formants; and grouping the plurality of candidate features includes an act of grouping the plurality of candidate features into the plurality of candidate feature sets for each of the plurality of frames such that each of the plurality of candidate feature sets includes at least one value representative of each of a first formant, a second formant and a third formant detected in the respective frame. 27. The computer readable medium of claim 26 , wherein the act of detecting includes an act of detecting at least one additional feature selected from the group consisting of: pitch, timbre, energy and spectral slope.
| 0.927461 |
4. The system of claim 3 , the interactive component requests user identity prior to the view generation component generating the human-machine interface.
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4. The system of claim 3 , the interactive component requests user identity prior to the view generation component generating the human-machine interface. 5. The system of claim 4 , the interactive component requests information relating to authorization of use of the human-machine interface and location of devices associated with the human-machine interface.
| 0.934987 |
72. A system as defined in claim 71, wherein the interrogation data characteristic statistics generated by the interrogation processor include a frequency distribution of characters found in the scanned record, a rate of occurrence for each character in the frequency distribution, and an entropy value of the scanned record; and the interrogation processor further comprises: means for completing a stabilization procedure comprising repeating the steps of selecting a current record block for scanning and generating a current set of the interrogation statistics, selecting a new record block, different from the current block, for scanning and generating a new set of the interrogation statistics, and comparing like statistics of the current set of statistics and the new set of statistics, until the difference between the like statistics is below a predetermined stabilization threshold value or the number of scanned record blocks equals a predetermined scanning limit value, and thereupon storing the new block in an interrogation buffer and storing the set of new interrogation statistics in the memory if the entropy value is below a predetermined entropy threshold value.
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72. A system as defined in claim 71, wherein the interrogation data characteristic statistics generated by the interrogation processor include a frequency distribution of characters found in the scanned record, a rate of occurrence for each character in the frequency distribution, and an entropy value of the scanned record; and the interrogation processor further comprises: means for completing a stabilization procedure comprising repeating the steps of selecting a current record block for scanning and generating a current set of the interrogation statistics, selecting a new record block, different from the current block, for scanning and generating a new set of the interrogation statistics, and comparing like statistics of the current set of statistics and the new set of statistics, until the difference between the like statistics is below a predetermined stabilization threshold value or the number of scanned record blocks equals a predetermined scanning limit value, and thereupon storing the new block in an interrogation buffer and storing the set of new interrogation statistics in the memory if the entropy value is below a predetermined entropy threshold value. 79. A system as defined in claim 72, further including: means for selecting dictionary segments until the total number of dictionary segments selected for the system-built dictionary is equal to a predetermined limit number.
| 0.820802 |
7. A terminal, comprising: a microphone; a set of sensors for collecting pieces of information related to surrounding environment; a display device; a communication device; and utterance information transmitting means, connected to said microphone, said set of sensors and said communication device, for transmitting utterance information containing a speech signal obtained from a signal output by said microphone upon reception of an utterance and pieces of information obtained from said set of sensors when said speech signal is obtained, to a prescribed speech processing server through said communication device, and for requesting speech recognition and a prescribed data processing on a result of recognition; further comprising: process result presenting means, connected to said communication device, for receiving a process result of said data processing transmitted from said speech processing server in response to said request, and for presenting the process result to a user; and utterance candidate recommendation list display means, receiving an utterance candidate recommendation list recommended as a plurality of utterance candidates from said speech processing server and displaying the list on said display device, and thereby for recommending utterance candidates to said user.
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7. A terminal, comprising: a microphone; a set of sensors for collecting pieces of information related to surrounding environment; a display device; a communication device; and utterance information transmitting means, connected to said microphone, said set of sensors and said communication device, for transmitting utterance information containing a speech signal obtained from a signal output by said microphone upon reception of an utterance and pieces of information obtained from said set of sensors when said speech signal is obtained, to a prescribed speech processing server through said communication device, and for requesting speech recognition and a prescribed data processing on a result of recognition; further comprising: process result presenting means, connected to said communication device, for receiving a process result of said data processing transmitted from said speech processing server in response to said request, and for presenting the process result to a user; and utterance candidate recommendation list display means, receiving an utterance candidate recommendation list recommended as a plurality of utterance candidates from said speech processing server and displaying the list on said display device, and thereby for recommending utterance candidates to said user. 9. The terminal according to claim 7 , further comprising: selecting means operable by a user for selecting any of the utterance candidates displayed by said utterance candidate recommendation list; and utterance text information transmitting means, responsive to selection of any of the utterance candidates in said utterance candidate recommendation list by said selecting means, for transmitting utterance text information including a text of the selected utterance candidate and pieces of information obtained from said set of sensors to a prescribed speech processing server through said communication device, and requesting said prescribed data processing on said utterance text information.
| 0.655726 |
16. The method as described in claim 11 wherein said location and said size of said first interface region are dependent on a location and size of said interface region of said written marking.
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16. The method as described in claim 11 wherein said location and said size of said first interface region are dependent on a location and size of said interface region of said written marking. 17. The method as described in claim 16 wherein a height of said first interface region is dependent on a height of said interface region of said written marking.
| 0.93929 |
23. A computer-based method for use in managing a service level associated with resources in a distributed information technology (IT) system based on financial terms, the method comprising the steps of: automatically constructing and maintaining, via a processor of a computer, an electronic contract that contains information pertaining to descriptions of one or more business transactions in IT terms, financial implications of one or more business transaction service levels, and reporting to be performed in one or more financial terms; automatically measuring, via the processor of the computer, the operation of at least one distributed element of the IT system in terms of one or more business metrics based on the electronic contract and based at least in part on input received from at least one agent nodule located in the at least one distributed element; automatically determining, via the processor of the computer, at least one financial optimization based at least part on the measured one or more business metrics of the at least one distributed element of the IT system and based at least in part on the electronic contract, the financial optimization being specified in the electronic contract at the time of construction such that, at the time the financial optimization is to be determined, the electronic contract is accessed to identify a particular financial metric of the financial optimization that is to be computed and to identify an operation for computing the particular financial metric, the one or more business metrics are converted to one or more financial equivalents wherein the one or more financial equivalents comprise a cost of a lost connection, a cost of down time, and a relationship between revenue and network latency; and automatically issuing, via the processor of the computer, at least one control command based on the at least one financial optimization, the command to be executed on the at least one distributed element by the at least one agent module located in the at least one distributed element.
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23. A computer-based method for use in managing a service level associated with resources in a distributed information technology (IT) system based on financial terms, the method comprising the steps of: automatically constructing and maintaining, via a processor of a computer, an electronic contract that contains information pertaining to descriptions of one or more business transactions in IT terms, financial implications of one or more business transaction service levels, and reporting to be performed in one or more financial terms; automatically measuring, via the processor of the computer, the operation of at least one distributed element of the IT system in terms of one or more business metrics based on the electronic contract and based at least in part on input received from at least one agent nodule located in the at least one distributed element; automatically determining, via the processor of the computer, at least one financial optimization based at least part on the measured one or more business metrics of the at least one distributed element of the IT system and based at least in part on the electronic contract, the financial optimization being specified in the electronic contract at the time of construction such that, at the time the financial optimization is to be determined, the electronic contract is accessed to identify a particular financial metric of the financial optimization that is to be computed and to identify an operation for computing the particular financial metric, the one or more business metrics are converted to one or more financial equivalents wherein the one or more financial equivalents comprise a cost of a lost connection, a cost of down time, and a relationship between revenue and network latency; and automatically issuing, via the processor of the computer, at least one control command based on the at least one financial optimization, the command to be executed on the at least one distributed element by the at least one agent module located in the at least one distributed element. 35. The method of claim 23 , wherein the one or more business metrics to monitor are inferred from the electronic contract.
| 0.563272 |
11. A communication device, including: a memory; at least one communications subsystem; and at least one processor configured to enable: receiving a first input comprising a first search keyword and at least one explicitly specified parameter value for use in a query to be transmitted to a first online service; in response to receiving a search command, generating a first query comprising the first search keyword and the at least one explicitly specified parameter value; transmitting the first query to the first online service; and storing the at least one explicitly specified parameter value in association with the first search keyword at the communication device; receiving a second input comprising a second search keyword for use in a query to be transmitted to the first online service or to another online service; and in response to receiving a further search command, generating a second query comprising the second search keyword; in response to determining that the second search keyword matches the first search keyword and that the second input does not include any explicitly specified parameter values, using one or more of the at least one explicitly specified parameter values associated with the first search keyword to modify the second query; and transmitting the modified second query to the first or other online service.
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11. A communication device, including: a memory; at least one communications subsystem; and at least one processor configured to enable: receiving a first input comprising a first search keyword and at least one explicitly specified parameter value for use in a query to be transmitted to a first online service; in response to receiving a search command, generating a first query comprising the first search keyword and the at least one explicitly specified parameter value; transmitting the first query to the first online service; and storing the at least one explicitly specified parameter value in association with the first search keyword at the communication device; receiving a second input comprising a second search keyword for use in a query to be transmitted to the first online service or to another online service; and in response to receiving a further search command, generating a second query comprising the second search keyword; in response to determining that the second search keyword matches the first search keyword and that the second input does not include any explicitly specified parameter values, using one or more of the at least one explicitly specified parameter values associated with the first search keyword to modify the second query; and transmitting the modified second query to the first or other online service. 13. The communication device of claim 11 , wherein the second search keyword is for use in a query to be transmitted to the first online service, and retrieving one or more of the at least one explicitly specified parameter value comprises retrieving all of the at least one explicitly specified parameter value stored in association with the first search keyword.
| 0.651919 |
1. A system for collection of activity data related to a plurality of authenticated computer network users, comprising: a data collection server, deployed within said computer network, configured to collect raw activity data related to said plurality of users from sources within said computer network, wherein said sources include at least some of a web content management server, a document management server, a web server, a proxy server, a directory service information server, an email server, or a client-side logging application, the data collection server being configured to normalize the raw activity data to provide normalized activity data associated with the document, wherein normalization of the raw activity data resolves differences of actions on the document by unifying saving the document, directly opening the document, and opening the document via textually different URLs such that the activity data reflects activity data associated with the document, wherein the textually different URLs are resolved to be logically equivalent by disassembling the textually different URLs and reconstructing a URL having a unified format; and a control server coupled to said data collection server, said control server having a processor and a memory storing at least one configuration table containing at least one rule based on which said control server is configured to regulate the collection, transformation, aggregation, and anonymization of said raw activity data related to said plurality of users to generate user activity data on said computer network in compliance with at least one privacy law and/or at least one organizational privacy policy, wherein personally identifiable information is removed from the user activity data, wherein said at least one rule includes a schedule to collect activity data from said sources and an exclusion rule which defines a subset of said plurality of users and/or sources from which collection of activity data is not allowed.
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1. A system for collection of activity data related to a plurality of authenticated computer network users, comprising: a data collection server, deployed within said computer network, configured to collect raw activity data related to said plurality of users from sources within said computer network, wherein said sources include at least some of a web content management server, a document management server, a web server, a proxy server, a directory service information server, an email server, or a client-side logging application, the data collection server being configured to normalize the raw activity data to provide normalized activity data associated with the document, wherein normalization of the raw activity data resolves differences of actions on the document by unifying saving the document, directly opening the document, and opening the document via textually different URLs such that the activity data reflects activity data associated with the document, wherein the textually different URLs are resolved to be logically equivalent by disassembling the textually different URLs and reconstructing a URL having a unified format; and a control server coupled to said data collection server, said control server having a processor and a memory storing at least one configuration table containing at least one rule based on which said control server is configured to regulate the collection, transformation, aggregation, and anonymization of said raw activity data related to said plurality of users to generate user activity data on said computer network in compliance with at least one privacy law and/or at least one organizational privacy policy, wherein personally identifiable information is removed from the user activity data, wherein said at least one rule includes a schedule to collect activity data from said sources and an exclusion rule which defines a subset of said plurality of users and/or sources from which collection of activity data is not allowed. 3. The system of claim 1 , further comprising: means for providing a graphical user interface to allow the editing of said at least one configuration table in order to comply with at least one of: a change in the at least one privacy law; and the at least one organizational privacy policy.
| 0.693701 |
33. A method for recognizing a speech pattern as a string of predetermined reference words comprising the steps of: storing a set of signals representative of the time frame sequence of acoustic features of each reference word from a beginning frame to an ending frame; producing a set of signals representative of the time frame sequence of acoustic features of the speech from a beginning frame to a final frame; generating at least one reference word string responsive to the feature signals of the reference words and the feature signals of the speech pattern; and identifying the speech pattern as one of said generated reference word strings; the reference word string generating step comprising: generating a set of signals to identify successive levels of said reference words, assigning a segment of the speech pattern to each successive reference word level, at each reference word level dynamically time warping the feature signals of each reference word with the feature signals of the speech pattern segment assigned to the level to produce signals representative of time registration path speech pattern endframes for said reference word and signals representative of the correspondence of the reference word and speech pattern segment feature signals along the time registration paths, and selecting strings of reference words responsive to the time registration path speech pattern endframe and correspondence signals of the levels.
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33. A method for recognizing a speech pattern as a string of predetermined reference words comprising the steps of: storing a set of signals representative of the time frame sequence of acoustic features of each reference word from a beginning frame to an ending frame; producing a set of signals representative of the time frame sequence of acoustic features of the speech from a beginning frame to a final frame; generating at least one reference word string responsive to the feature signals of the reference words and the feature signals of the speech pattern; and identifying the speech pattern as one of said generated reference word strings; the reference word string generating step comprising: generating a set of signals to identify successive levels of said reference words, assigning a segment of the speech pattern to each successive reference word level, at each reference word level dynamically time warping the feature signals of each reference word with the feature signals of the speech pattern segment assigned to the level to produce signals representative of time registration path speech pattern endframes for said reference word and signals representative of the correspondence of the reference word and speech pattern segment feature signals along the time registration paths, and selecting strings of reference words responsive to the time registration path speech pattern endframe and correspondence signals of the levels. 34. A method for recognizing a speech pattern as a string of predetermined reference words according to claim 33 wherein said dynamic time warping step further comprises: selecting for each speech pattern endframe signal the time registration path having the minimum correspondence signal at said endframe responsive to the reference word time registration endframe and correspondence signals of each level; storing for each speech pattern endframe signal, a signal identifying the reference word with the minimum correspondence signal time registration path, the minimum correspondence signal and a signal representative of the starting frame of the minimum correspondence time registration path.
| 0.533586 |
18. A system for providing multi-media conferencing, the system comprising one or more processors having: a conference scheduling application configured to receive textual information for display during a conference session among a plurality of participants, and to retrieve configuration information specifying language assistance for the textual information, wherein the configuration information is associated with one of the participants; and a language assistance application configured to augment the textual information according to the configuration information for comprehension of the textual information by the one participant, wherein the language assistance application determines whether the textual information is contained in a predetermined list of terms and associated supplemental information, and if the textual information is in the list, the language assistance application marks the textual information to notify the one participant that the supplemental information is available for selective display, the supplemental information including definitions of the corresponding terms, and wherein the textual information having the marking is forwarded to the one participant for display during the conference session without replacement of the textual information.
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18. A system for providing multi-media conferencing, the system comprising one or more processors having: a conference scheduling application configured to receive textual information for display during a conference session among a plurality of participants, and to retrieve configuration information specifying language assistance for the textual information, wherein the configuration information is associated with one of the participants; and a language assistance application configured to augment the textual information according to the configuration information for comprehension of the textual information by the one participant, wherein the language assistance application determines whether the textual information is contained in a predetermined list of terms and associated supplemental information, and if the textual information is in the list, the language assistance application marks the textual information to notify the one participant that the supplemental information is available for selective display, the supplemental information including definitions of the corresponding terms, and wherein the textual information having the marking is forwarded to the one participant for display during the conference session without replacement of the textual information. 30. A system according to claim 18 , wherein an icon displayed to the one participant is responsive to at least one of the start time of the conference session, the stop time of the conference or the duration of the conference.
| 0.562953 |
1. An image processing apparatus in which embedded information in input document data is detected and an image processing is carried out in accordance with a result of detection of the embedded information, the image processing apparatus comprising: a CPU; and a non-transitory storage medium tangibly embodying a program of instructions executable by the CPU to configure the CPU to include: a document input mechanism configured to receive input document data including image data, the document input mechanism comprising a fixed portion consisting of an extraction of common control portions for plural input document types including scanned document, stored/read document, received document from an arbitrary input source and media document specialized for a particular client, wherein the document input mechanism inherits from the fixed portion, and is developed such that the document input mechanism inheriting from the fixed portion is dynamically added; an embedded information analysis mechanism connected to the document input mechanism via a first interface, and configured to analyze embedded information in the received input document data, to determine an analysis result; a behavior determination mechanism connected to the embedded information analysis mechanism via a second interface, and configured to determine a behavior rule based on the analysis result and output behavior rule information; a document output mechanism connected to the behavior determination mechanism via a third interface, and configured to determine, based on the behavior rule information received from the behavior determination mechanism, a processing to be applied to the input document data; and an image management mechanism connected to the document output mechanism via a fourth interface and to the document input mechanism via a fifth interface to receive the input document data, and configured to manage the input document data in accordance with instruction received from the document output mechanism, wherein the document output mechanism determines the instruction to output to the image management mechanism based on the processing to be applied to the input document data; wherein two of the first through fifth interfaces associated with any one of the mechanisms, including the document input mechanism, embedded information analysis mechanism, behavior determination mechanism, document output mechanism and image management mechanism, are fixed and are not changed even when said one of the mechanisms connected to the two interfaces is replaced by a substitute mechanism.
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1. An image processing apparatus in which embedded information in input document data is detected and an image processing is carried out in accordance with a result of detection of the embedded information, the image processing apparatus comprising: a CPU; and a non-transitory storage medium tangibly embodying a program of instructions executable by the CPU to configure the CPU to include: a document input mechanism configured to receive input document data including image data, the document input mechanism comprising a fixed portion consisting of an extraction of common control portions for plural input document types including scanned document, stored/read document, received document from an arbitrary input source and media document specialized for a particular client, wherein the document input mechanism inherits from the fixed portion, and is developed such that the document input mechanism inheriting from the fixed portion is dynamically added; an embedded information analysis mechanism connected to the document input mechanism via a first interface, and configured to analyze embedded information in the received input document data, to determine an analysis result; a behavior determination mechanism connected to the embedded information analysis mechanism via a second interface, and configured to determine a behavior rule based on the analysis result and output behavior rule information; a document output mechanism connected to the behavior determination mechanism via a third interface, and configured to determine, based on the behavior rule information received from the behavior determination mechanism, a processing to be applied to the input document data; and an image management mechanism connected to the document output mechanism via a fourth interface and to the document input mechanism via a fifth interface to receive the input document data, and configured to manage the input document data in accordance with instruction received from the document output mechanism, wherein the document output mechanism determines the instruction to output to the image management mechanism based on the processing to be applied to the input document data; wherein two of the first through fifth interfaces associated with any one of the mechanisms, including the document input mechanism, embedded information analysis mechanism, behavior determination mechanism, document output mechanism and image management mechanism, are fixed and are not changed even when said one of the mechanisms connected to the two interfaces is replaced by a substitute mechanism. 4. The image processing apparatus according to claim 1 , wherein the second and third interfaces are fixed, and when the behavior determination mechanism is replaced with another behavior determination mechanism that conforms to the second and third interfaces during image processing, the other mechanisms, including the document input mechanism, embedded information analysis mechanism, document output mechanism and image management mechanism, are not affected.
| 0.501332 |
8. The method of claim 6 , wherein representing the distinct book content items as a graph in computer memory comprises: representing the book content items as a weighted graph in the computer memory, the weighted graph including a plurality of distinct nodes, each distinct node representing a corresponding distinct book content item in the plurality of distinct book content items, each edge in the weighted graph being weighted based on a relative importance of the distinct node from which the edge originates; for each distinct node: identifying matching image content in image content of other distinct book content items that are represented by other distinct nodes, each matching image content being image content that has descriptor points that match the corresponding descriptor points of image content in the distinct book content item corresponding to the distinct node; generating edges in the weighted graph connecting the distinct node to other distinct nodes corresponding to the other distinct book content items, each edge representing one or more matches of image content in the distinct book content item to matching image content in another distinct book content item.
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8. The method of claim 6 , wherein representing the distinct book content items as a graph in computer memory comprises: representing the book content items as a weighted graph in the computer memory, the weighted graph including a plurality of distinct nodes, each distinct node representing a corresponding distinct book content item in the plurality of distinct book content items, each edge in the weighted graph being weighted based on a relative importance of the distinct node from which the edge originates; for each distinct node: identifying matching image content in image content of other distinct book content items that are represented by other distinct nodes, each matching image content being image content that has descriptor points that match the corresponding descriptor points of image content in the distinct book content item corresponding to the distinct node; generating edges in the weighted graph connecting the distinct node to other distinct nodes corresponding to the other distinct book content items, each edge representing one or more matches of image content in the distinct book content item to matching image content in another distinct book content item. 9. The method of claim 8 , wherein identifying matching image content in the image content of other distinct book content items comprises identifying image content in the other distinct book content items having descriptor points that exactly match the descriptor points of image content in the distinct book content item corresponding to the distinct node.
| 0.632771 |
13. An apparatus for generating a text sentence in a target language different in a source language, based on one or more words in the source language input as keywords, the apparatus comprising: input apparatus for inputting one or more keywords in the source language without inputting a full text sentence in the source language, the one or more keywords being a segment of the full text sentence in the source language; a parallel corpus database including partial correspondence information indicating correspondence between a word/phrase in the source language and a word/phrase in the target language in each sentence pair; a sentence pair extraction means for extracting one or more sentence pairs each including more than one of the keywords from the parallel corpus database; a keyword-related phrase storage means for detecting a target-language keyword-related phrase corresponding to each source-language keyword-related phrase from the partial correspondence information of each sentence pair and storing the detected target-language keyword-related phrase in the form of a keyword-related phrase table; a text candidate generation means that performs dependency relationships of each keyword-related phrases in the source language and in the target language of the pair of keyword-related phrases described in the keyword-related phrase table and generates one or more target-language sentence candidates by using a target language keyword-related phrase generation model and a language model by assuming dependency relationships or two or more pairs of keyword-related phrases; and an output means for outputting at least one text sentence candidate corresponding to the full text sentence in the source language.
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13. An apparatus for generating a text sentence in a target language different in a source language, based on one or more words in the source language input as keywords, the apparatus comprising: input apparatus for inputting one or more keywords in the source language without inputting a full text sentence in the source language, the one or more keywords being a segment of the full text sentence in the source language; a parallel corpus database including partial correspondence information indicating correspondence between a word/phrase in the source language and a word/phrase in the target language in each sentence pair; a sentence pair extraction means for extracting one or more sentence pairs each including more than one of the keywords from the parallel corpus database; a keyword-related phrase storage means for detecting a target-language keyword-related phrase corresponding to each source-language keyword-related phrase from the partial correspondence information of each sentence pair and storing the detected target-language keyword-related phrase in the form of a keyword-related phrase table; a text candidate generation means that performs dependency relationships of each keyword-related phrases in the source language and in the target language of the pair of keyword-related phrases described in the keyword-related phrase table and generates one or more target-language sentence candidates by using a target language keyword-related phrase generation model and a language model by assuming dependency relationships or two or more pairs of keyword-related phrases; and an output means for outputting at least one text sentence candidate corresponding to the full text sentence in the source language. 22. The apparatus of claim 13 , wherein, in the text candidate generation means that performs dependency relationships of each keyword-related phrase in the source language and in the target language of the pair of keyword-related phrases described in the keyword-related phrase table and generates one or more target-language sentence candidates by using a target language keyword-related phrase generation model and a language model by assuming dependency relationships of two or more pairs of keyword-related phrases, the target language keyword-related phrase generation model depends on the type of information used and includes a trigram, a backward trigram, and one or more modified word sequences.
| 0.811532 |
1. A system for searching through a corpus by using a query, the corpus comprising a plurality of items, and the system comprising: a first computer hosting a server node, the first computer comprising a processor and a non-transitory memory to store instructions; and a second computer hosting a user interface node in communication with the first computer, wherein the second computer is configured to receive a first query input and to transmit the first query input to the first computer; wherein the processor executes the instructions to: use the received first query input to determine a first search term corresponding to a subject of the query and to prompt a user for entry of a second query input after receiving the first query input, by causing first known relationships corresponding to the first search term to be listed, wherein the subject corresponds to a class type, property, name, or literal that matches the first query input; use the received second query input to determine a second search term corresponding to a predicate of the query and to prompt the user for entry of a third query input, after receiving the second query input, by causing second known relationships corresponding to the second search term to be listed, wherein the predicate is one of the first known relationships corresponding to the first search term; use the received third query input to determine a third search term corresponding to an object of the query, wherein the object corresponds to a class type, person, or location within a range of the second search term; use the first, second, and third search terms to determine a contextual relationship therebetween; and use the query formed by the first, second, and third search terms and the determined contextual relationship to perform a first comparison against the corpus to determine a ranked list of results.
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1. A system for searching through a corpus by using a query, the corpus comprising a plurality of items, and the system comprising: a first computer hosting a server node, the first computer comprising a processor and a non-transitory memory to store instructions; and a second computer hosting a user interface node in communication with the first computer, wherein the second computer is configured to receive a first query input and to transmit the first query input to the first computer; wherein the processor executes the instructions to: use the received first query input to determine a first search term corresponding to a subject of the query and to prompt a user for entry of a second query input after receiving the first query input, by causing first known relationships corresponding to the first search term to be listed, wherein the subject corresponds to a class type, property, name, or literal that matches the first query input; use the received second query input to determine a second search term corresponding to a predicate of the query and to prompt the user for entry of a third query input, after receiving the second query input, by causing second known relationships corresponding to the second search term to be listed, wherein the predicate is one of the first known relationships corresponding to the first search term; use the received third query input to determine a third search term corresponding to an object of the query, wherein the object corresponds to a class type, person, or location within a range of the second search term; use the first, second, and third search terms to determine a contextual relationship therebetween; and use the query formed by the first, second, and third search terms and the determined contextual relationship to perform a first comparison against the corpus to determine a ranked list of results. 6. The system of claim 1 , wherein the processor further executes the instructions to: determine at least one suggested alternative search term to at least one of the first, second, and third search terms; transmit the at least one suggested alternative search term to the user interface node; receive an acceptance of the at least one suggested alternative search term from the user interface node; use the accepted alternative search term to determine a modified contextual relationship between the search terms and to form a modified query; and use the modified query and the modified contextual relationship to perform a second comparison against the corpus to determine a modified list of results.
| 0.5 |
1. A method for categorizing interactions in a call center of an organization, comprising: capturing in the call center at least one vocal interaction and at least one non-vocal interaction, using logging or capturing devices, wherein the at least one vocal interaction and the at least one non-vocal interaction are captured in accordance with pre-defined rules that regulate which interaction is to be captured, and wherein the at least one vocal interaction and the at least one non-vocal interaction having dissimilar contents of common semantic context; retrieving at least one first word from the at least one vocal interaction; retrieving at least one second word from the at least one non-vocal interaction; assigning the at least one vocal interaction into a first category, wherein the first category is based on technical data of the at least one vocal interaction, using the at least one first word; assigning the at least one non-vocal interaction into a second category, wherein the second category is based on technical data of the at least one non-vocal interaction, using the at least one second word; and associating the first category and the second category into a multi-channel category based on the common semantic context thereof, thus aggregating the at least one vocal interaction and the at least one non-vocal interaction.
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1. A method for categorizing interactions in a call center of an organization, comprising: capturing in the call center at least one vocal interaction and at least one non-vocal interaction, using logging or capturing devices, wherein the at least one vocal interaction and the at least one non-vocal interaction are captured in accordance with pre-defined rules that regulate which interaction is to be captured, and wherein the at least one vocal interaction and the at least one non-vocal interaction having dissimilar contents of common semantic context; retrieving at least one first word from the at least one vocal interaction; retrieving at least one second word from the at least one non-vocal interaction; assigning the at least one vocal interaction into a first category, wherein the first category is based on technical data of the at least one vocal interaction, using the at least one first word; assigning the at least one non-vocal interaction into a second category, wherein the second category is based on technical data of the at least one non-vocal interaction, using the at least one second word; and associating the first category and the second category into a multi-channel category based on the common semantic context thereof, thus aggregating the at least one vocal interaction and the at least one non-vocal interaction. 11. The method of claim 1 further comprising analyzing the multi-channel category.
| 0.586355 |
1. A computer-implemented method, comprising: storing, at a server system, a set of previously trained predicative models; storing, at the server system, a respective performance indicator associated with each predictive model in the set of predictive models, where each of the respective performance indicators comprises a quantifiable metric determined based on prior usage data corresponding to the associated predictive model; receiving, at the server system, a first feature vector from a first remote computing device, the first feature vector comprising one or more elements; identifying, using the server system, an element type for each of the one or more elements of the first feature vector; selecting, using the server system, a first subset of predictive models from the set of predictive models, where the selection is based on the identified element types of the first feature vector and the stored performance indicators associated with the predictive models of the set; processing the first feature vector using the first subset of predictive models, each predictive model of the first subset of predictive models generating a respective predictive output based on the first feature vector to provide a first plurality of predictive outputs; generating a first combined predictive output based on the first plurality of predictive outputs; in response to generating the first combined predictive output, evaluating a performance of at least one predictive model of the subset; and updating the performance indicator associated with the at least one predictive model based on the evaluated performance.
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1. A computer-implemented method, comprising: storing, at a server system, a set of previously trained predicative models; storing, at the server system, a respective performance indicator associated with each predictive model in the set of predictive models, where each of the respective performance indicators comprises a quantifiable metric determined based on prior usage data corresponding to the associated predictive model; receiving, at the server system, a first feature vector from a first remote computing device, the first feature vector comprising one or more elements; identifying, using the server system, an element type for each of the one or more elements of the first feature vector; selecting, using the server system, a first subset of predictive models from the set of predictive models, where the selection is based on the identified element types of the first feature vector and the stored performance indicators associated with the predictive models of the set; processing the first feature vector using the first subset of predictive models, each predictive model of the first subset of predictive models generating a respective predictive output based on the first feature vector to provide a first plurality of predictive outputs; generating a first combined predictive output based on the first plurality of predictive outputs; in response to generating the first combined predictive output, evaluating a performance of at least one predictive model of the subset; and updating the performance indicator associated with the at least one predictive model based on the evaluated performance. 11. The method of claim 1 , wherein processing the first feature vector comprises submitting at least a portion of the first feature vector to each predictive model of the first subset of predictive models in parallel.
| 0.711327 |
9. The method of claim 1 , wherein the searching the memory is performed for the second keyword.
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9. The method of claim 1 , wherein the searching the memory is performed for the second keyword. 10. The method of claim 9 , wherein the searching the memory comprises: querying a news clip directory where the second keyword is related to a current event; and querying an encyclopedia where the second keyword is not related to a current event.
| 0.920513 |
1. A method for partitioning a video sequence, comprising: dividing a video sequence into a plurality of segments; generating a transcript of speech content of the video sequence, wherein the transcript comprises a plurality of words and identifies temporal locations of the words in the video sequence; selecting a plurality of keywords from the plurality of words in the transcript; selecting a set of keywords from the plurality of keywords, wherein the keywords in the set of keywords are related to each other by meanings of the keywords; determining a distribution of occurrences across the plurality of segments of the keywords in the set of keywords; selecting a group of segments from the plurality of segments using the distribution, wherein the segments in the group of segments are temporally adjacent and the group of segments corresponds to a peak of the occurrences across the plurality of segments of the keywords in the set of keywords; and forming a partition of the video sequence from the group of segments; wherein generating the transcript of speech content of the video sequence comprises generating the transcript from audio content of the video sequence using automatic speech recognition, determining whether the transcript generated from the audio content is satisfactory, responsive to a determination that the transcript generated from the audio content is not satisfactory, determining whether the video sequence has closed caption, and responsive to a determination that the video sequence has closed caption, generating the transcript from the closed caption.
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1. A method for partitioning a video sequence, comprising: dividing a video sequence into a plurality of segments; generating a transcript of speech content of the video sequence, wherein the transcript comprises a plurality of words and identifies temporal locations of the words in the video sequence; selecting a plurality of keywords from the plurality of words in the transcript; selecting a set of keywords from the plurality of keywords, wherein the keywords in the set of keywords are related to each other by meanings of the keywords; determining a distribution of occurrences across the plurality of segments of the keywords in the set of keywords; selecting a group of segments from the plurality of segments using the distribution, wherein the segments in the group of segments are temporally adjacent and the group of segments corresponds to a peak of the occurrences across the plurality of segments of the keywords in the set of keywords; and forming a partition of the video sequence from the group of segments; wherein generating the transcript of speech content of the video sequence comprises generating the transcript from audio content of the video sequence using automatic speech recognition, determining whether the transcript generated from the audio content is satisfactory, responsive to a determination that the transcript generated from the audio content is not satisfactory, determining whether the video sequence has closed caption, and responsive to a determination that the video sequence has closed caption, generating the transcript from the closed caption. 4. The method of claim 1 , wherein each of the keywords is a type of keyword selected from the group of types of keywords consisting of a single word and a phrase.
| 0.919316 |
1. A method of populating a database, comprising: a) providing a plurality of information files, wherein each information file includes an object, each object including a type, an object property and an object explicit relationship; b) providing a plurality of rule files, wherein each rule file includes a relation between at least two object types, each relation including a relation property and an explicit relationship definition; c) validating the object properties and the object explicit relationships based in part on the relation properties, the explicit relationship definitions, or both; d) determining at least one implicit relationship based on at least one of the explicit relationship definitions and at least one of the object explicit relationships; e) generating at least one Structured Query Language (SQL) command representative of the at least one implicit relationship; f) executing the generated at least one SQL command on a database to store an implicit relationship definition in the form of a SQL statement; g) selecting an object from the information files; and h) generating a document by populating a presentation template with the object property of the selected object, the document having at least one hypertext link to a second document, the link based on the stored implicit relationship definition.
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1. A method of populating a database, comprising: a) providing a plurality of information files, wherein each information file includes an object, each object including a type, an object property and an object explicit relationship; b) providing a plurality of rule files, wherein each rule file includes a relation between at least two object types, each relation including a relation property and an explicit relationship definition; c) validating the object properties and the object explicit relationships based in part on the relation properties, the explicit relationship definitions, or both; d) determining at least one implicit relationship based on at least one of the explicit relationship definitions and at least one of the object explicit relationships; e) generating at least one Structured Query Language (SQL) command representative of the at least one implicit relationship; f) executing the generated at least one SQL command on a database to store an implicit relationship definition in the form of a SQL statement; g) selecting an object from the information files; and h) generating a document by populating a presentation template with the object property of the selected object, the document having at least one hypertext link to a second document, the link based on the stored implicit relationship definition. 18. The method of claim 1 , further comprising generating an inventory file that describes each object included in the information files.
| 0.647554 |
1. An apparatus for dynamic Web page performance scoring, comprising: a tool for accessing Web page structure in connection with the real time loading, display, and operation of a Web page; said tool comprising a module for analyzing a plurality of Web page metrics related to said Web page while said Web page is running; said tool comprising a module for receiving information about said Web page that is generated while analyzing said Web page metrics; said tool comprising a heuristic mechanism for calculating a performance subscore for each of said metrics; and said tool comprising a module for combining said performance subscores for said metrics to produce at least one interpretable Web page performance score.
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1. An apparatus for dynamic Web page performance scoring, comprising: a tool for accessing Web page structure in connection with the real time loading, display, and operation of a Web page; said tool comprising a module for analyzing a plurality of Web page metrics related to said Web page while said Web page is running; said tool comprising a module for receiving information about said Web page that is generated while analyzing said Web page metrics; said tool comprising a heuristic mechanism for calculating a performance subscore for each of said metrics; and said tool comprising a module for combining said performance subscores for said metrics to produce at least one interpretable Web page performance score. 10. The apparatus of claim 1 , said heuristic mechanism using user data, connection data, and DOM data for generating a first-load and second-load score for a browser.
| 0.605459 |
1. A method for utilizing content rich analytical data, comprising: obtaining informational content via multiple channels including at least one of RSS feeds, news feeds, web content aggregators, web engines, social networking medias, search engines, online ad engines, banner engines, online news groups, and forums; storing the informational content in a Darwin Information Typing Architecture database in a native extensible markup language format, the stored informational content including at least one of interactive objects, media files, hotspots, and extensible markup language cross-references; capturing an audit trail during a user session; grouping a subset of correlated actions within the audit trail as a transaction by: capturing an opening action performed by an end user on one or more publishing servers using a client device associated with the end user, the client device communicatively coupled with the one or more publishing servers via a network, the one or more publishing servers adapted to publish informational content to the end user, the opening action performed by the client device on a document, determining actual informational content provided to the end user by applying a filter key associated with the informational content, generating a unique transaction key in response to the captured opening action performed by the client device on the document, correlating a subsequent XML cross referencing (XREF) action that is performed by the client device to the document opening action via the transaction key, the XML cross referencing action and created EXREF event relative to opening of the document, evaluating a natural language of informational content of the document opened by the client device, and generating a natural language preference for the natural language of the document based on the opening action and the correlated cross reference action; generating content rich analytical data from the audit trail, the content rich analytical data filtered and formatted based on a plurality of preferences that include the generated natural language preference generated from behavior of the end user including opening actions of the end user; obtaining informational content for the end user from the informational content stored in the database; translating the obtained informational content according to a language that corresponds to the generated natural language preference of the end user as determined from the content rich analytical data generated from the audit trail; reformatting the native extensible markup language format of the obtained informational content obtained from the database according to the generated natural language preference of the end user in a format for use by a web browser of the user client device to display the obtained informational content on the client device in a format that is perceivable to the end user; and providing the translated and formatted informational content to the end user.
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1. A method for utilizing content rich analytical data, comprising: obtaining informational content via multiple channels including at least one of RSS feeds, news feeds, web content aggregators, web engines, social networking medias, search engines, online ad engines, banner engines, online news groups, and forums; storing the informational content in a Darwin Information Typing Architecture database in a native extensible markup language format, the stored informational content including at least one of interactive objects, media files, hotspots, and extensible markup language cross-references; capturing an audit trail during a user session; grouping a subset of correlated actions within the audit trail as a transaction by: capturing an opening action performed by an end user on one or more publishing servers using a client device associated with the end user, the client device communicatively coupled with the one or more publishing servers via a network, the one or more publishing servers adapted to publish informational content to the end user, the opening action performed by the client device on a document, determining actual informational content provided to the end user by applying a filter key associated with the informational content, generating a unique transaction key in response to the captured opening action performed by the client device on the document, correlating a subsequent XML cross referencing (XREF) action that is performed by the client device to the document opening action via the transaction key, the XML cross referencing action and created EXREF event relative to opening of the document, evaluating a natural language of informational content of the document opened by the client device, and generating a natural language preference for the natural language of the document based on the opening action and the correlated cross reference action; generating content rich analytical data from the audit trail, the content rich analytical data filtered and formatted based on a plurality of preferences that include the generated natural language preference generated from behavior of the end user including opening actions of the end user; obtaining informational content for the end user from the informational content stored in the database; translating the obtained informational content according to a language that corresponds to the generated natural language preference of the end user as determined from the content rich analytical data generated from the audit trail; reformatting the native extensible markup language format of the obtained informational content obtained from the database according to the generated natural language preference of the end user in a format for use by a web browser of the user client device to display the obtained informational content on the client device in a format that is perceivable to the end user; and providing the translated and formatted informational content to the end user. 15. The method according to claim 1 , further comprising: comparing the generated analytical data to informational content in a database; and dynamically generating informational content that corresponds to at least a portion of the analytical data by selecting informational content from the database.
| 0.534905 |
17. A speech recognition system comprising: a primary speech processor that processes an audio signal comprising a spoken utterance of a plurality of uttered characters, wherein the processing comprises determining an identified character sequence by determining corresponding identified characters for individual ones of the plurality of uttered characters; and a character post-processor that selects a plurality of known character sequences that potentially correspond to the identified character sequence and, for each selected known character sequence, scores such known character sequence based at least in part on a weighting of individual characters that comprise the known character sequence, wherein the character post-processor selects a value that corresponds to a second character of the known character sequence in response to determining that the second character of the known character sequence matches a first identified character of the identified character sequence, and adds the selected value to a cumulative score associated with the known character sequence.
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17. A speech recognition system comprising: a primary speech processor that processes an audio signal comprising a spoken utterance of a plurality of uttered characters, wherein the processing comprises determining an identified character sequence by determining corresponding identified characters for individual ones of the plurality of uttered characters; and a character post-processor that selects a plurality of known character sequences that potentially correspond to the identified character sequence and, for each selected known character sequence, scores such known character sequence based at least in part on a weighting of individual characters that comprise the known character sequence, wherein the character post-processor selects a value that corresponds to a second character of the known character sequence in response to determining that the second character of the known character sequence matches a first identified character of the identified character sequence, and adds the selected value to a cumulative score associated with the known character sequence. 20. The system of claim 17 , wherein the selected value is pre-assigned in a character set to the second character.
| 0.680412 |
19. A computer system that previews a content package file containing references to content files, the computer system comprising: a portal server that fetches references to content files from the content package file, wherein the content files are separate files from the content package file, fetches the content files associated with the references, replaces the references to the content files with content extracted from the content files to create a combined file, removes the references from the combined file; and creates a preview screen of the content package file and the content files using the combined file; and a client that displays the preview screen, wherein information rendered by the preview screen displays at least some of the content extracted from the first level content files and content from the content package file, wherein the preview screen displays a version of the content package file modified with content from the combined file, wherein the preview screen displays the modified version of the content package file prior to the portal server importing the content package file and the content files from the client.
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19. A computer system that previews a content package file containing references to content files, the computer system comprising: a portal server that fetches references to content files from the content package file, wherein the content files are separate files from the content package file, fetches the content files associated with the references, replaces the references to the content files with content extracted from the content files to create a combined file, removes the references from the combined file; and creates a preview screen of the content package file and the content files using the combined file; and a client that displays the preview screen, wherein information rendered by the preview screen displays at least some of the content extracted from the first level content files and content from the content package file, wherein the preview screen displays a version of the content package file modified with content from the combined file, wherein the preview screen displays the modified version of the content package file prior to the portal server importing the content package file and the content files from the client. 24. The computer system according to claim 19 wherein the preview screen displays meta-data about the content files.
| 0.553918 |
1. A system for sharing security information, the system comprising: a plurality of entities, wherein each entity of the plurality of entities comprises a network of computing devices; and one or more computing devices programmed, via executable code instructions, to: share a first plurality of security attack data, the first plurality of security attack data comprising information regarding one or more first security attacks; receive a ruleset from a first entity of the plurality of entities, the ruleset comprising instructions selectably applicable by an entity of the plurality of entities to detect one or more security attacks, wherein the ruleset is generated by the first entity, and wherein the ruleset is associated with the first plurality of security attack data; and apply the ruleset at a second entity of the plurality of entities to identify malicious behavior of a potential or actual security attack, wherein applying the ruleset comprises: identifying a plurality of network communications associated with a network of computing devices of the second entity, wherein the plurality of network communications are from the network of computing devices of the second entity to an external computing device; identifying an elapsed time between at least two communications of the plurality of network communications; and determining that the elapsed time is within a predetermined time interval, wherein said determination indicates beaconing behavior.
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1. A system for sharing security information, the system comprising: a plurality of entities, wherein each entity of the plurality of entities comprises a network of computing devices; and one or more computing devices programmed, via executable code instructions, to: share a first plurality of security attack data, the first plurality of security attack data comprising information regarding one or more first security attacks; receive a ruleset from a first entity of the plurality of entities, the ruleset comprising instructions selectably applicable by an entity of the plurality of entities to detect one or more security attacks, wherein the ruleset is generated by the first entity, and wherein the ruleset is associated with the first plurality of security attack data; and apply the ruleset at a second entity of the plurality of entities to identify malicious behavior of a potential or actual security attack, wherein applying the ruleset comprises: identifying a plurality of network communications associated with a network of computing devices of the second entity, wherein the plurality of network communications are from the network of computing devices of the second entity to an external computing device; identifying an elapsed time between at least two communications of the plurality of network communications; and determining that the elapsed time is within a predetermined time interval, wherein said determination indicates beaconing behavior. 7. The system of claim 1 , wherein the one or more computing devices is further programmed, via executable code instructions, to: access second security attack data associated with a second potential or actual security attack directed at the second entity; access redaction rules of the second entity, wherein the redaction rules are associated with at least one of: internal IP addresses, hostnames, or other identifying information of a network of computing devices of the second entity; generate modified security attack data from the second security attack data by removing any matching internal IP addresses, hostnames, or other identifying information as indicated by the redaction rules; and share the modified security attack data with a third entity.
| 0.5 |
24. The system of claim 23 , further comprising: means for repeating said applying each of a plurality of functions step for a predetermined number of events to capture a window of events as a window example; and means for sequentially shifting said window down one event at a time until a final event within said database falls within said window.
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24. The system of claim 23 , further comprising: means for repeating said applying each of a plurality of functions step for a predetermined number of events to capture a window of events as a window example; and means for sequentially shifting said window down one event at a time until a final event within said database falls within said window. 25. The system of claim 24 , further comprising: means for applying current policy rules base to determine a labeling for each event window example; means for labeling an event window selected by a user for override of an initial labeling to produce a set of re-labeled event example windows; and means for applying theory refinement to the set of re-labeled event example windows to generate a new policy document that is consistent with the re-labeled event example windows.
| 0.828326 |
7. The computer readable storage medium of claim 1 , wherein the content on the website comprises a complete set of results for the query run by a web service.
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7. The computer readable storage medium of claim 1 , wherein the content on the website comprises a complete set of results for the query run by a web service. 8. The computer readable storage medium of claim 7 , wherein the one or more keywords is retrieved from a subset of the complete set of results for the query.
| 0.947849 |
1. A method comprising: creating a design environment for a user, said design environment configured to display a design, and said design environment allowing said user to apply a design font to a portion of text in said design; providing said user with the ability to define a mapping from said design font to a target font; receiving said mapping from said user while said user is creating said design; generating a markup language representation of said design; and applying said mapping to said design; wherein said design font is linked to said portion of text in said design: (i) continuously before and after said mapping is received from said user, and (ii) using an encoding prior to said generating step; said portion of text in said design is not displayed using said target font while said design is edited in said design environment; said target font is linked to said portion of text in said markup language representation using a different encoding; and said portion of text in said markup language representation is displayed using said target font while said design is rendered outside of the design environment in an external player or inside the design environment in a virtual external player instantiated within the design environment.
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1. A method comprising: creating a design environment for a user, said design environment configured to display a design, and said design environment allowing said user to apply a design font to a portion of text in said design; providing said user with the ability to define a mapping from said design font to a target font; receiving said mapping from said user while said user is creating said design; generating a markup language representation of said design; and applying said mapping to said design; wherein said design font is linked to said portion of text in said design: (i) continuously before and after said mapping is received from said user, and (ii) using an encoding prior to said generating step; said portion of text in said design is not displayed using said target font while said design is edited in said design environment; said target font is linked to said portion of text in said markup language representation using a different encoding; and said portion of text in said markup language representation is displayed using said target font while said design is rendered outside of the design environment in an external player or inside the design environment in a virtual external player instantiated within the design environment. 2. The method of claim 1 , wherein: said mapping maps a full published version of said design font to said target font; and said mapping is applied during said generating step.
| 0.5 |
10. The computer-implemented method of claim 1 , wherein the indexed semantic user profile associated with the particular user is determined at least in part based on a static user profile of the particular user.
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10. The computer-implemented method of claim 1 , wherein the indexed semantic user profile associated with the particular user is determined at least in part based on a static user profile of the particular user. 13. The computer-implemented method of claim 10 , wherein the static user profile is generated by an external process or service.
| 0.872951 |
1. A method for filtering messages, the method comprising: receiving a message over a network communication interface; executing instructions stored in memory, the instructions being executed by a processor to: process the received message using one or more reliable classifiers that are associated with a higher level of accuracy than at least one trained classifier from a plurality of available classifiers, wherein the one or more reliable classifiers are associated with a feature count, classify the received message using the one or more reliable classifiers and the feature count, track a feature of the classified message based on the classification, wherein the tracked feature and one or more other tracked features are stored in a table and the feature count accounts for a number of times the tracked feature appeared in the classified message, and process the received message based on the classification, wherein processing of the received message includes blocking the received message when the received message is classified as spam or allowing the received message to be forwarded to a recipient when the message is classified as a good message; receiving a new indication that the message is spam or good, the new indication regarding a different feature count associated with a different feature; updating the trained classifier by updating the feature count in accordance with the different feature count in the new indication; identifying that a subsequently received message is spam based on the updated feature count and a whitelist count, wherein the whitelist count is associated with a number of times that at least one of the feature or the different feature appears in one or more whitelisted messages; and blocking the subsequently received message based on the subsequently received message being classified as spam in accordance with the updated feature count.
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1. A method for filtering messages, the method comprising: receiving a message over a network communication interface; executing instructions stored in memory, the instructions being executed by a processor to: process the received message using one or more reliable classifiers that are associated with a higher level of accuracy than at least one trained classifier from a plurality of available classifiers, wherein the one or more reliable classifiers are associated with a feature count, classify the received message using the one or more reliable classifiers and the feature count, track a feature of the classified message based on the classification, wherein the tracked feature and one or more other tracked features are stored in a table and the feature count accounts for a number of times the tracked feature appeared in the classified message, and process the received message based on the classification, wherein processing of the received message includes blocking the received message when the received message is classified as spam or allowing the received message to be forwarded to a recipient when the message is classified as a good message; receiving a new indication that the message is spam or good, the new indication regarding a different feature count associated with a different feature; updating the trained classifier by updating the feature count in accordance with the different feature count in the new indication; identifying that a subsequently received message is spam based on the updated feature count and a whitelist count, wherein the whitelist count is associated with a number of times that at least one of the feature or the different feature appears in one or more whitelisted messages; and blocking the subsequently received message based on the subsequently received message being classified as spam in accordance with the updated feature count. 13. The method of claim 1 , wherein the at least one other classifier from the plurality of available classifiers are also used to further classify the received message when the one or more reliable classifiers are unable to classify the received message.
| 0.5 |
12. The method of claim 10 further comprising: after identifying the individual breadcrumbs, identifying noise among the individual breadcrumbs; and removing noise before forming the breadcrumb search strings.
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12. The method of claim 10 further comprising: after identifying the individual breadcrumbs, identifying noise among the individual breadcrumbs; and removing noise before forming the breadcrumb search strings. 13. The method of claim 12 further comprising: receiving a list of noise words; comparing the individual breadcrumbs with the list of noise words; and if an individual breadcrumb matches a noise word on the list of noise words, removing the noise-matching individual breadcrumb from the individual breadcrumbs.
| 0.912371 |
1. A method for recommending search phrases, comprising: obtaining one or more subject terms and one or more descriptive terms relating to the one or more subject terms from title information of information published by publishers; combining at least some of the one or more subject terms with at least some of the one or more descriptive terms to form a set of one or more search phrases; calculating a first appraisal value for a search phrase among the set of one or more search phrases, the calculating of the first appraisal value comprising multiplying term frequency of the search phrase with an inverse document frequency of the search phrase; determining a second appraisal value of the search phrase, the determining of the second appraisal value comprising: calculating an inverse class frequency of the search phrase within a designated category, wherein the inverse class frequency is regarded as the second appraisal value; calculating a third appraisal value of the search phrase, comprising: calculating a first probability that a first term appears in a search phrase associated with the published information; calculating a second probability that the first term appears jointly with a second term in the search phrase associated with the published information; and combining the first probability and the second probability to obtain the third appraisal value; combining at least the first appraisal value, the second appraisal value, and the third appraisal value of the search phrase to obtain a publisher recommendation appraisal value for the search phrase; and selecting a recommended phrase among the set of one or more search phrases based at least in part on a set of one or more corresponding publisher recommendation appraisal values for the set of one or more search phrases.
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1. A method for recommending search phrases, comprising: obtaining one or more subject terms and one or more descriptive terms relating to the one or more subject terms from title information of information published by publishers; combining at least some of the one or more subject terms with at least some of the one or more descriptive terms to form a set of one or more search phrases; calculating a first appraisal value for a search phrase among the set of one or more search phrases, the calculating of the first appraisal value comprising multiplying term frequency of the search phrase with an inverse document frequency of the search phrase; determining a second appraisal value of the search phrase, the determining of the second appraisal value comprising: calculating an inverse class frequency of the search phrase within a designated category, wherein the inverse class frequency is regarded as the second appraisal value; calculating a third appraisal value of the search phrase, comprising: calculating a first probability that a first term appears in a search phrase associated with the published information; calculating a second probability that the first term appears jointly with a second term in the search phrase associated with the published information; and combining the first probability and the second probability to obtain the third appraisal value; combining at least the first appraisal value, the second appraisal value, and the third appraisal value of the search phrase to obtain a publisher recommendation appraisal value for the search phrase; and selecting a recommended phrase among the set of one or more search phrases based at least in part on a set of one or more corresponding publisher recommendation appraisal values for the set of one or more search phrases. 16. The method as described in claim 1 , wherein the search phrase includes a descriptive term, a subject term, or a combination thereof.
| 0.954455 |
14. A method to control access to information, the method comprising: computer hardware generating a modified list of index terms by encrypting one or more tokens occurring in a first type of field of a first document using a first set of encryption settings; the computer hardware executing an indexing step using the modified list of index terms; the computer hardware generating a modified list of search terms by adding to a list of search terms one or both of synonyms of the search terms and terms that are related to the search terms; the computer hardware removing frequently used words from the modified list of search terms; and responsive to a determination that a user has authorization to view the first type of field, the computer hardware adding to the modified list of search terms an encrypted version of a search term included in the list of search terms such that execution of a search using the modified list of search terms returns a result that identifies the first document as a search result when either an unencrypted or an encrypted version of that search term is found in the index terms associated with the first document.
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14. A method to control access to information, the method comprising: computer hardware generating a modified list of index terms by encrypting one or more tokens occurring in a first type of field of a first document using a first set of encryption settings; the computer hardware executing an indexing step using the modified list of index terms; the computer hardware generating a modified list of search terms by adding to a list of search terms one or both of synonyms of the search terms and terms that are related to the search terms; the computer hardware removing frequently used words from the modified list of search terms; and responsive to a determination that a user has authorization to view the first type of field, the computer hardware adding to the modified list of search terms an encrypted version of a search term included in the list of search terms such that execution of a search using the modified list of search terms returns a result that identifies the first document as a search result when either an unencrypted or an encrypted version of that search term is found in the index terms associated with the first document. 16. The method of claim 14 , the method further including: a computer hardware determining that a second type of field of a second document has restricted access, based on a first degree of authorization of the user; the computer hardware generating a modified list of index terms by encrypting one or more tokens occurring in the second type of field using a second set of encryption settings; and the computer hardware executing an indexing step using the modified list of index terms.
| 0.678834 |
1. An artificial neural network for processing data, comprising at least one processing unit, a first processing unit including (a) at least one artificial neuronal encoder for encoding a vector into a neuronal code; (b) a means for evaluating a code deviation vector that is the deviation of a neuronal code obtained by said artificial neuronal encoder from a neuronal code average; (c) a plurality of artificial synapse memories each for storing a component of a code deviation accumulation vector; (d) a first means for evaluating a first product of a component of a code deviation accumulation vector, a masking factor, and a component of a code deviation vector; (e) an artificial nonspiking neuron processor for evaluating a first sum of first products obtained by said first means; (f) a plurality of artificial synapse memories each for storing an entry of a code covariance matrix; (g) a second means for evaluating a second product of an entry of a code covariance matrix, a masking factor, and a component of a code deviation vector; and (h) at least one artificial spiking neuron processor for evaluating a second sum of second products obtained by said second means, and for using at least said second sum and a first sum obtained by said artificial nonspiking neuron processor to evaluate a representation of a first empirical probability distribution of a component of a label of a vector that is input to said first processing unit.
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1. An artificial neural network for processing data, comprising at least one processing unit, a first processing unit including (a) at least one artificial neuronal encoder for encoding a vector into a neuronal code; (b) a means for evaluating a code deviation vector that is the deviation of a neuronal code obtained by said artificial neuronal encoder from a neuronal code average; (c) a plurality of artificial synapse memories each for storing a component of a code deviation accumulation vector; (d) a first means for evaluating a first product of a component of a code deviation accumulation vector, a masking factor, and a component of a code deviation vector; (e) an artificial nonspiking neuron processor for evaluating a first sum of first products obtained by said first means; (f) a plurality of artificial synapse memories each for storing an entry of a code covariance matrix; (g) a second means for evaluating a second product of an entry of a code covariance matrix, a masking factor, and a component of a code deviation vector; and (h) at least one artificial spiking neuron processor for evaluating a second sum of second products obtained by said second means, and for using at least said second sum and a first sum obtained by said artificial nonspiking neuron processor to evaluate a representation of a first empirical probability distribution of a component of a label of a vector that is input to said first processing unit. 7. The artificial neural network of claim 1 , said first processing unit further including (a) a third means for evaluating a third product of a component of a code deviation accumulation vector, a learning masking factor, and a component of a code deviation vector; (b) a summing means for evaluating a third sum of third products obtained by said third means; (c) a fourth means for evaluating a fourth product of an entry of a code covariance matrix, a learning masking factor, and a component of a code deviation vector; (d) a summing-evaluating means for evaluating a fourth sum of fourth products obtained by said fourth means and for using at least said fourth sum and a third sum obtained by said summing means to evaluate a representation of a second empirical probability distribution of a component of a label of a vector that is input to said first processing unit; and (e) an unsupervised learning means for using at least a pseudorandom number generated in accordance with a second empirical probability distribution generated by said summing-evaluation means and a component of a code deviation vector to adjust an entry of a code covariance matrix by an unsupervised covariance rule in response to a vector that is input to said first processing unit.
| 0.5 |
13. The user interface of claim 12 including: selection means for providing a view from the at least one additional display of the hierarchy contents which contents are related to the search term or a selected further search term from the list space.
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13. The user interface of claim 12 including: selection means for providing a view from the at least one additional display of the hierarchy contents which contents are related to the search term or a selected further search term from the list space. 15. The user interface of claim 13 wherein said selection means is means responsive to selection of a further search term.
| 0.892065 |
1. A method in a group manager of a central service node, of enabling services or media in a communication network, comprising the following steps: detecting activities and conditions of communication devices in the network, for each of a plurality of entities, collecting individual context data relating to the entity, the individual context data comprising a first data value corresponding to a first behavioral context parameter, and a second data value corresponding to a first environmental context parameter, wherein first behavioral context parameter is separate and distinct from the first environmental context parameter, for each of the plurality of said entities, creating an individual context vector for said entity from said collected individual context data related to said entity, wherein each of said plurality of context vectors identifies a point in a logical, as opposed to a physical, N-dimensional space, where N is greater than or equal to two, creating a master context vector comprising a third data value corresponding to the first behavioral context parameter, and a fourth data value corresponding to the first environmental context parameter, wherein the master context vector identifies a centroid point in the logical N-dimensional space, for each of the plurality of said individual context vectors, determining the distance between the centroid point and the point identified by said individual context vector, defining a group of correlated entities that are found to be correlated with respect to one or more features or characteristics based on the collected individual context data by including an entity in the group in response to determining that the distance between the centroid point and the point identified by said individual context vector corresponding to said entity is less than a threshold.
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1. A method in a group manager of a central service node, of enabling services or media in a communication network, comprising the following steps: detecting activities and conditions of communication devices in the network, for each of a plurality of entities, collecting individual context data relating to the entity, the individual context data comprising a first data value corresponding to a first behavioral context parameter, and a second data value corresponding to a first environmental context parameter, wherein first behavioral context parameter is separate and distinct from the first environmental context parameter, for each of the plurality of said entities, creating an individual context vector for said entity from said collected individual context data related to said entity, wherein each of said plurality of context vectors identifies a point in a logical, as opposed to a physical, N-dimensional space, where N is greater than or equal to two, creating a master context vector comprising a third data value corresponding to the first behavioral context parameter, and a fourth data value corresponding to the first environmental context parameter, wherein the master context vector identifies a centroid point in the logical N-dimensional space, for each of the plurality of said individual context vectors, determining the distance between the centroid point and the point identified by said individual context vector, defining a group of correlated entities that are found to be correlated with respect to one or more features or characteristics based on the collected individual context data by including an entity in the group in response to determining that the distance between the centroid point and the point identified by said individual context vector corresponding to said entity is less than a threshold. 8. The method according to claim 1 , wherein the selected context parameters of relevance to the group define the common characteristics of the group, which is manifested in a Group Profile that can be used as a basis for producing adapted communication services or media for the group.
| 0.77648 |
1. A computer-implemented method for validating an entity, the method comprising: classifying an entity type of an entity to be validated based on a predefined entity classifier; selecting at least one of a plurality of validation rules in accordance with the entity type; producing, by a computer of a requesting entity and based on the selected at least one validation rule, a validation request including information identifying the entity; providing, by the computer, the validation request to a validation entity for performance of at least a portion of a validation in accordance with the selected at least one validation rule; receiving, by the computer, a validation outcome of the at least the portion of the validation from the validation entity; generating a validation request management display including an inbox icon, an outbox icon, an overview section, and a details section; wherein: responsive to selection of the inbox icon, the overview section displays a list of validation outcomes that have been received and the details section displays detailed information regarding a selected one of the listed validation outcomes; and responsive to selection of the outbox icon, the overview section displays a list of validation requests that have been provided to validation entities and the details section displays detailed information regarding a selected one of the listed validation requests.
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1. A computer-implemented method for validating an entity, the method comprising: classifying an entity type of an entity to be validated based on a predefined entity classifier; selecting at least one of a plurality of validation rules in accordance with the entity type; producing, by a computer of a requesting entity and based on the selected at least one validation rule, a validation request including information identifying the entity; providing, by the computer, the validation request to a validation entity for performance of at least a portion of a validation in accordance with the selected at least one validation rule; receiving, by the computer, a validation outcome of the at least the portion of the validation from the validation entity; generating a validation request management display including an inbox icon, an outbox icon, an overview section, and a details section; wherein: responsive to selection of the inbox icon, the overview section displays a list of validation outcomes that have been received and the details section displays detailed information regarding a selected one of the listed validation outcomes; and responsive to selection of the outbox icon, the overview section displays a list of validation requests that have been provided to validation entities and the details section displays detailed information regarding a selected one of the listed validation requests. 18. The method of claim 1 , wherein the displayed detailed information regarding the selected one of the listed validation outcomes includes questions answered by the validation entity when a first view button of the details section is selected and includes answers to the questions when a second view button of the details section is selected.
| 0.5 |
28. A method for loading data from a spreadsheet dataset, having data in the form of one or more records, into a database comprising: a) creating a control file having rules, each rule including a condition, wherein the rules describe mappings between attributes of the spreadsheet dataset and attributes of a business object; b) inputting the spreadsheet dataset and the control file into a spreadsheet loader; c) evaluating each rule with respect to each record to determine if the condition for the rule is true for that record and if the condition is true, then parsing the record into one or more tokens and referencing values for each of the one or more tokens using a value clause of the rule, wherein each of the values is associated with one of the attributes of the business object; d) sending the parsed, valued data to the database, wherein the parsed, valued data is stored in the database using a data access layer comprising an entity definition and a persistence map, wherein the entity definition defines the business object based on attributes of the database and the persistence map defines how the parsed, valued data is stored in the database.
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28. A method for loading data from a spreadsheet dataset, having data in the form of one or more records, into a database comprising: a) creating a control file having rules, each rule including a condition, wherein the rules describe mappings between attributes of the spreadsheet dataset and attributes of a business object; b) inputting the spreadsheet dataset and the control file into a spreadsheet loader; c) evaluating each rule with respect to each record to determine if the condition for the rule is true for that record and if the condition is true, then parsing the record into one or more tokens and referencing values for each of the one or more tokens using a value clause of the rule, wherein each of the values is associated with one of the attributes of the business object; d) sending the parsed, valued data to the database, wherein the parsed, valued data is stored in the database using a data access layer comprising an entity definition and a persistence map, wherein the entity definition defines the business object based on attributes of the database and the persistence map defines how the parsed, valued data is stored in the database. 41. A method as in claim 28 , wherein the set of rules in the control file contain a variable rule and an entity rule.
| 0.721114 |
1. A computer-implemented method, the method comprising: receiving a request for sponsored content for presentation with a multimedia content item, wherein the content item is included in a document; selecting a plurality of keywords for the content item wherein a first keyword of the keywords is selected based on historical user interaction with the content item when the content item was provided as a search result responsive to a query comprising the first keyword, and wherein a second keyword of the keywords is selected based on analysis of the content item; for each of one or more candidate sponsored content items: calculating a respective first score based at least partially on a comparison of the candidate sponsored content item to one or more of the keywords; calculating a respective second score based on, at least, a comparison of the candidate sponsored content item to content of the document and based on a profile of an owner of the document; calculating a respective final score based on, at least, a weighted combination of the respective first and second scores in which the first and second scores are weighted differently, and in which a weight of the first or the second score is based at least partially on a measure of past user interactions with the candidate sponsored content item when the candidate sponsored content item was presented with the content item; selecting one or more of the candidate sponsored content items based on, at least, the candidate sponsored content items' respective final scores; and providing the selected sponsored content items for presentation with the content item.
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1. A computer-implemented method, the method comprising: receiving a request for sponsored content for presentation with a multimedia content item, wherein the content item is included in a document; selecting a plurality of keywords for the content item wherein a first keyword of the keywords is selected based on historical user interaction with the content item when the content item was provided as a search result responsive to a query comprising the first keyword, and wherein a second keyword of the keywords is selected based on analysis of the content item; for each of one or more candidate sponsored content items: calculating a respective first score based at least partially on a comparison of the candidate sponsored content item to one or more of the keywords; calculating a respective second score based on, at least, a comparison of the candidate sponsored content item to content of the document and based on a profile of an owner of the document; calculating a respective final score based on, at least, a weighted combination of the respective first and second scores in which the first and second scores are weighted differently, and in which a weight of the first or the second score is based at least partially on a measure of past user interactions with the candidate sponsored content item when the candidate sponsored content item was presented with the content item; selecting one or more of the candidate sponsored content items based on, at least, the candidate sponsored content items' respective final scores; and providing the selected sponsored content items for presentation with the content item. 2. The method of claim 1 , wherein the sponsored content items comprise one or more advertisements.
| 0.581682 |
17. An apparatus comprising: a processor; and non-transitory memory storing computer readable instructions that, when executed, cause the apparatus to: transmit a content item to a first location; identify a plurality of desired portions of the content item at a location remote from said first location; create one or more annotations for the content item, the one or more annotations including a pointer corresponding to a desired portion of the plurality of desired portions and displayable content information describing a non-identified portion of the content item, wherein the displayable content information is different from the content item; and transmit, from the location remote from said first location, the one or more annotations to another device, including the pointer and the displayable content information, wherein the one or more annotations are configured to cause the other device to generate a display of the displayable content information along with one or more of the plurality of desired portions.
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17. An apparatus comprising: a processor; and non-transitory memory storing computer readable instructions that, when executed, cause the apparatus to: transmit a content item to a first location; identify a plurality of desired portions of the content item at a location remote from said first location; create one or more annotations for the content item, the one or more annotations including a pointer corresponding to a desired portion of the plurality of desired portions and displayable content information describing a non-identified portion of the content item, wherein the displayable content information is different from the content item; and transmit, from the location remote from said first location, the one or more annotations to another device, including the pointer and the displayable content information, wherein the one or more annotations are configured to cause the other device to generate a display of the displayable content information along with one or more of the plurality of desired portions. 18. The apparatus of claim 17 , wherein the one or more annotations are transmitted subsequent to the content item being provided at a specified time.
| 0.550442 |
5. At least one computer-readable storage device encoded with a speech synthesis program which causes a system for synthesizing speech from text to perform: determining a first speech segment sequence corresponding to an input text, by selecting speech segments from the speech segment database according to a first cost calculated based at least in part on a statistical model of prosody variations; determining prosody modification values for the first speech segment sequence, after the first speech segment sequence is selected, by using a second cost calculated based at least in part on the statistical model of prosody variations, wherein the first cost is different from the second cost; and applying the determined prosody modification values to the first speech segment sequence to produce a second speech segment sequence whose prosodic characteristics are different from prosodic characteristics of the first speech segment sequence, wherein the second cost includes at least a prosody modification cost, the program further causing the system to perform the step of increasing the prosody modification cost of continuous speech segments having a slope likelihood greater than a given value in the first speech segment sequence before determining the prosody modification values in response to detection of the continuous speech segments.
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5. At least one computer-readable storage device encoded with a speech synthesis program which causes a system for synthesizing speech from text to perform: determining a first speech segment sequence corresponding to an input text, by selecting speech segments from the speech segment database according to a first cost calculated based at least in part on a statistical model of prosody variations; determining prosody modification values for the first speech segment sequence, after the first speech segment sequence is selected, by using a second cost calculated based at least in part on the statistical model of prosody variations, wherein the first cost is different from the second cost; and applying the determined prosody modification values to the first speech segment sequence to produce a second speech segment sequence whose prosodic characteristics are different from prosodic characteristics of the first speech segment sequence, wherein the second cost includes at least a prosody modification cost, the program further causing the system to perform the step of increasing the prosody modification cost of continuous speech segments having a slope likelihood greater than a given value in the first speech segment sequence before determining the prosody modification values in response to detection of the continuous speech segments. 7. The at least one computer readable storage device of claim 5 , wherein the second cost for determining the prosody modification values includes an absolute frequency likelihood cost, the frequency slope likelihood cost, a frequency linear approximation error cost, and a prosody modification cost.
| 0.553364 |
10. The method according to claim 9 , wherein said recalling of said duplicate documents is done in real-time.
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10. The method according to claim 9 , wherein said recalling of said duplicate documents is done in real-time. 11. The method according to claim 10 , wherein recalling said duplicate documents includes an access control defining a level of accessibility of a user, said selection is based on said access control for said recalled documents and said level of accessibility of the user.
| 0.951795 |
8. A method of analyzing speech comprising the steps of generating electrical signals representative of the spoken vocabulary words and portions of spoken vocabulary words of a predetermined finite vocabulary with the vocabulary words being included into units containing a plurality of phonemes or phoneme groups, time quantizing the amplitude of the electrical signals into digital form, selectively compressing the time quantized signals by discarding selected portions of them while substantially simultaneously generating instruction signals as to which portions have been discarded, and storing selected portions of the digital signals representative of phonemes and phoneme groups in a first, addressable memory, storing the instruction signals in a second, addressable memory including instruction signals as to the sequence of addresses of the stored phonemes and phoneme groups necessary to reproduce words and sentences of the vocabulary, wherein the signal compressing and storing steps include the following steps: (a) selecting signals representative of certain phonemes and phoneme groups from the time quantized signals and replacing portions of these selected signals corresponding to parts of the pitch periods of the certain phonemes and phoneme groups by a constant amplitude signal while generating instruction signals as to which phonemes and phoneme groups have been so selected, and (b) Fourier transforming the time quantized signals to generate a set of discrete amplitudes and phase angles, adjusting the phase angles so that the inverse Fourier transformation of the amplitudes and new phases is symmetric, inverse Fourier transforming the phase adjusted amplitudes and phases, storing one-half of a selected waveform as representative of each discrete set of phase adjusted amplitudes and phases and discarding the other half of the selected waveform.
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8. A method of analyzing speech comprising the steps of generating electrical signals representative of the spoken vocabulary words and portions of spoken vocabulary words of a predetermined finite vocabulary with the vocabulary words being included into units containing a plurality of phonemes or phoneme groups, time quantizing the amplitude of the electrical signals into digital form, selectively compressing the time quantized signals by discarding selected portions of them while substantially simultaneously generating instruction signals as to which portions have been discarded, and storing selected portions of the digital signals representative of phonemes and phoneme groups in a first, addressable memory, storing the instruction signals in a second, addressable memory including instruction signals as to the sequence of addresses of the stored phonemes and phoneme groups necessary to reproduce words and sentences of the vocabulary, wherein the signal compressing and storing steps include the following steps: (a) selecting signals representative of certain phonemes and phoneme groups from the time quantized signals and replacing portions of these selected signals corresponding to parts of the pitch periods of the certain phonemes and phoneme groups by a constant amplitude signal while generating instruction signals as to which phonemes and phoneme groups have been so selected, and (b) Fourier transforming the time quantized signals to generate a set of discrete amplitudes and phase angles, adjusting the phase angles so that the inverse Fourier transformation of the amplitudes and new phases is symmetric, inverse Fourier transforming the phase adjusted amplitudes and phases, storing one-half of a selected waveform as representative of each discrete set of phase adjusted amplitudes and phases and discarding the other half of the selected waveform. 9. A method of analyzing speech as recited in claim 8 wherein in the method further comprises differentiating the electrical signals with respect to time prior to the time quantization step.
| 0.829533 |
1. A machine-implemented method comprising: receiving into a memory of a computer system, data representing a plurality of query terms arranged in a plurality of sets of query terms; accessing, with the computer system, an electronic database including computer readable storage that stores data representing items of sponsored content, wherein each item of sponsored content has associated a plurality of item terms, and the computer readable storage further stores data representing the plurality of item terms associated with the sponsored content; using one or more processors in the computer system, for each of the items of sponsored content: identifying a set of matched query terms using a matching operation between the plurality of query terms and the plurality of item terms associated with the item of sponsored content, wherein each of the plurality of sets of query terms comprises at least one query term that matches at least one item term of the plurality of item terms associated with the item of sponsored content; formulating a score for the item of sponsored content according to the set of matched query terms, wherein a value for each of the matched query terms is determined based on a number of sets in which the each of the matched query terms resides, weighted based on a set in which the each of the matched query terms resides, and the score of the item is determined by combining values for all the matched query terms; identifying, from the identified matched query terms for the item of sponsored content, one or more unique query terms that are included in (i) the identified set of matched query terms and (ii) more than one set of the plurality of sets of query terms; determining a number of the one or more unique query terms across sets of the plurality of sets of query terms; adjusting the score for the item of sponsored content as a function of the determined number of the one or more unique query terms; and assigning the adjusted score to the item of sponsored content.
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1. A machine-implemented method comprising: receiving into a memory of a computer system, data representing a plurality of query terms arranged in a plurality of sets of query terms; accessing, with the computer system, an electronic database including computer readable storage that stores data representing items of sponsored content, wherein each item of sponsored content has associated a plurality of item terms, and the computer readable storage further stores data representing the plurality of item terms associated with the sponsored content; using one or more processors in the computer system, for each of the items of sponsored content: identifying a set of matched query terms using a matching operation between the plurality of query terms and the plurality of item terms associated with the item of sponsored content, wherein each of the plurality of sets of query terms comprises at least one query term that matches at least one item term of the plurality of item terms associated with the item of sponsored content; formulating a score for the item of sponsored content according to the set of matched query terms, wherein a value for each of the matched query terms is determined based on a number of sets in which the each of the matched query terms resides, weighted based on a set in which the each of the matched query terms resides, and the score of the item is determined by combining values for all the matched query terms; identifying, from the identified matched query terms for the item of sponsored content, one or more unique query terms that are included in (i) the identified set of matched query terms and (ii) more than one set of the plurality of sets of query terms; determining a number of the one or more unique query terms across sets of the plurality of sets of query terms; adjusting the score for the item of sponsored content as a function of the determined number of the one or more unique query terms; and assigning the adjusted score to the item of sponsored content. 3. The machine-implemented method of claim 1 , wherein adjusting the score includes determining a score penalty based on the determined number of the one or more unique query terms.
| 0.604554 |
23. The system of claim 16 , in which the processor determines the semantic zoom display of the one or more citations based on transformations of the plurality of sections.
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23. The system of claim 16 , in which the processor determines the semantic zoom display of the one or more citations based on transformations of the plurality of sections. 25. The system of claim 23 , in which the transformations are performed upon the data comprising at least one of characters, words and phrases contained in the plurality of sections.
| 0.932507 |
1. A method for using input signal quality to improve speech recognition, comprising: obtaining quantitative measurements of the quality of an input signal of a speech recognition system, the quantitative measurements including at least a signal-to-noise ratio and a loudness of the input signal; analyzing the quantitative measurements to categorize the quality of the input signal into a qualitative category; and establishing a rejection threshold used in rejecting a speech recognition result for speech included in the input signal in dependence on the qualitative category of the input signal quality, the speech recognition result having a confidence score indicating a level of confidence in an accuracy of the speech recognition result, the rejection threshold establishing which confidence scores indicate that the speech recognition result is to be rejected as being incorrectly recognized.
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1. A method for using input signal quality to improve speech recognition, comprising: obtaining quantitative measurements of the quality of an input signal of a speech recognition system, the quantitative measurements including at least a signal-to-noise ratio and a loudness of the input signal; analyzing the quantitative measurements to categorize the quality of the input signal into a qualitative category; and establishing a rejection threshold used in rejecting a speech recognition result for speech included in the input signal in dependence on the qualitative category of the input signal quality, the speech recognition result having a confidence score indicating a level of confidence in an accuracy of the speech recognition result, the rejection threshold establishing which confidence scores indicate that the speech recognition result is to be rejected as being incorrectly recognized. 3. The method of claim 1 , wherein, if the qualitative category of the input signal indicates that the input signal quality is high, establishing the rejection threshold comprises increasing a baseline rejection threshold.
| 0.526071 |
7. A computer-implemented method comprising: receiving an initial set of terms of a query from a user of a computer via an interface of the computer; initializing a set of candidate terms and storing the terms in a non-transitory, tangible memory of the computer; performing the following for a predetermined number of iterations: obtaining a predetermined number of temporary terms for each candidate term of the set of candidate terms, the predetermined number of temporary terms having the highest differential affinity to the each candidate term, wherein the differential affinity for the temporary term with respect to a candidate term is the differential affinity between the temporary term and the candidate term minus the average affinity of the temporary term; placing each temporary term and the associated differential affinity into a set of temporary terms, if a temporary term is obtained from more than one candidate term, the differential affinity of the temporary term being related to the differential affinities to the more than one candidate term; calculating an average differential affinity for each temporary term of the set of temporary terms, the average differential affinity representing an average of differential affinities from the each temporary term to every term of the initial set of terms; removing form the temporary set one or more terms with an average differential affinity that fails to satisfy a predetermined threshold; and placing one or more terms of the temporary set with differential affinities above the threshold into the set of candidate terms; selecting one or more terms of the set of candidate terms; and outputting the one or more selected terms to the user via the interface.
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7. A computer-implemented method comprising: receiving an initial set of terms of a query from a user of a computer via an interface of the computer; initializing a set of candidate terms and storing the terms in a non-transitory, tangible memory of the computer; performing the following for a predetermined number of iterations: obtaining a predetermined number of temporary terms for each candidate term of the set of candidate terms, the predetermined number of temporary terms having the highest differential affinity to the each candidate term, wherein the differential affinity for the temporary term with respect to a candidate term is the differential affinity between the temporary term and the candidate term minus the average affinity of the temporary term; placing each temporary term and the associated differential affinity into a set of temporary terms, if a temporary term is obtained from more than one candidate term, the differential affinity of the temporary term being related to the differential affinities to the more than one candidate term; calculating an average differential affinity for each temporary term of the set of temporary terms, the average differential affinity representing an average of differential affinities from the each temporary term to every term of the initial set of terms; removing form the temporary set one or more terms with an average differential affinity that fails to satisfy a predetermined threshold; and placing one or more terms of the temporary set with differential affinities above the threshold into the set of candidate terms; selecting one or more terms of the set of candidate terms; and outputting the one or more selected terms to the user via the interface. 12. The method of claim 7 , the steps perform by a search engine executed by the computer.
| 0.913002 |
2. A method as recited in claim 1 , wherein said method further comprises: eliminating from said plurality of message types a second message type when said determining determines that said second message type should not be used for said unified message.
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2. A method as recited in claim 1 , wherein said method further comprises: eliminating from said plurality of message types a second message type when said determining determines that said second message type should not be used for said unified message. 3. A method as recited in claim 2 , wherein said method further comprises: providing one or more states for each one of said one or more features associated with said unified message.
| 0.881328 |
1. A method of processing speech, the method comprising: receiving a spoken utterance of a plurality of uttered characters; determining an identified character sequence by determining corresponding identified characters for individual ones of the plurality of uttered characters; selecting a plurality of known character sequences that potentially correspond to the identified character sequence; and for each selected known character sequence, scoring such known character sequence, using a processor, based at least in part on a weighting of individual characters that comprise the known character sequence, wherein scoring the known character sequence comprises: responsive to determining that a first character of the known character sequence matches a second identified character of the identified character sequence, selecting a value that corresponds to the first character of the known character sequence; and adding the selected value to a cumulative score associated with the known character sequence.
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1. A method of processing speech, the method comprising: receiving a spoken utterance of a plurality of uttered characters; determining an identified character sequence by determining corresponding identified characters for individual ones of the plurality of uttered characters; selecting a plurality of known character sequences that potentially correspond to the identified character sequence; and for each selected known character sequence, scoring such known character sequence, using a processor, based at least in part on a weighting of individual characters that comprise the known character sequence, wherein scoring the known character sequence comprises: responsive to determining that a first character of the known character sequence matches a second identified character of the identified character sequence, selecting a value that corresponds to the first character of the known character sequence; and adding the selected value to a cumulative score associated with the known character sequence. 2. The method of claim 1 , wherein the weighting is based at least in part on frequencies of utterance of the individual characters.
| 0.771478 |
6. The method of claim 3 , wherein the decay function is configured to determine weights for relational events based on social time.
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6. The method of claim 3 , wherein the decay function is configured to determine weights for relational events based on social time. 7. The method of claim 6 , wherein the decay function is configured to determine weights for the one or more relational events contained in the selected subset of relational events by determining a weight for a first relational event based on a number of relational events in the selected subset that occurred between the first relational event and a second relational event.
| 0.903093 |
9. A computer-implemented method performed by a computer-implemented system for processing a user interaction from a device of the user over a computer network, the interaction including text requiring recognition before being usable for further computer-implemented processing, the method comprising: receiving data representing the text from an application; dynamically selecting one or more recognizers from: a language model; and a human agent using a device located at a location remote from the computer-implemented system; and providing a recognition result responsive to results of processing by the selected recognizer.
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9. A computer-implemented method performed by a computer-implemented system for processing a user interaction from a device of the user over a computer network, the interaction including text requiring recognition before being usable for further computer-implemented processing, the method comprising: receiving data representing the text from an application; dynamically selecting one or more recognizers from: a language model; and a human agent using a device located at a location remote from the computer-implemented system; and providing a recognition result responsive to results of processing by the selected recognizer. 13. The computer-implemented method of claim 9 , wherein said dynamically selecting favors selection of the language model relative to the human agent based on recognition cost factors.
| 0.633376 |
1. An apparatus implemented with a processor and a memory, the apparatus to convert data, the apparatus comprising: a parser module configured to parse a data file having one or more data lines; a format module configured to automatically format the data file such that the formatted data file can be translated by a translator, the formatted data file comprising one or more computer language instructions; the translator configured to translate the formatted data file, the translator translating the formatted data file into one of object code, assembly language, and machine language; an output module configured to output the formatted data file as an output file; and a package module configured to package the translated output file as a searchable mainframe load module, the searchable load module compatible with a load library operating on a legacy computer system executing a mainframe operating system, the load library configured to return a file without a complete path name in response to a load command.
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1. An apparatus implemented with a processor and a memory, the apparatus to convert data, the apparatus comprising: a parser module configured to parse a data file having one or more data lines; a format module configured to automatically format the data file such that the formatted data file can be translated by a translator, the formatted data file comprising one or more computer language instructions; the translator configured to translate the formatted data file, the translator translating the formatted data file into one of object code, assembly language, and machine language; an output module configured to output the formatted data file as an output file; and a package module configured to package the translated output file as a searchable mainframe load module, the searchable load module compatible with a load library operating on a legacy computer system executing a mainframe operating system, the load library configured to return a file without a complete path name in response to a load command. 8. The apparatus of claim 1 , wherein the format module modifies the data file to allow processing of special symbols having syntax meaning to the translator.
| 0.553975 |
1. A method, comprising: receiving document fetch data of one or more document providers, document fetch data of a document provider comprising one or more document fetch parameters corresponding to document fetch operations associated with the document provider; grouping two or more document providers into a provider cluster based upon at least some document fetch data; and specifying a profile for the provider cluster based upon at least some document fetch parameters of the two or more document providers, the profile comprising one or more parameters corresponding to at least one of a document size parameter, a frequency http status code parameter, a mime type parameter or a redirect rate parameter.
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1. A method, comprising: receiving document fetch data of one or more document providers, document fetch data of a document provider comprising one or more document fetch parameters corresponding to document fetch operations associated with the document provider; grouping two or more document providers into a provider cluster based upon at least some document fetch data; and specifying a profile for the provider cluster based upon at least some document fetch parameters of the two or more document providers, the profile comprising one or more parameters corresponding to at least one of a document size parameter, a frequency http status code parameter, a mime type parameter or a redirect rate parameter. 6. The method of claim 1 , comprising: performing a plurality of current document fetch operations to a first document provider within the provider cluster to generate computed current document fetch parameters; comparing the computed current document fetch parameters associated with the first document provider with parameters of the profile associated with the provider cluster comprising the first document provider; and if the comparison indicates a discrepancy between the computed current document fetch parameters and at least some of the one or more of the parameters of the profile, then generating an alert.
| 0.620064 |
7. A telecommunications system, comprising: a local area network (LAN); a multimedia server operably coupled to said network, said multimedia server adapted to manage a multimedia conference and including a memory for storing selectable portions of said multimedia conference; one or more client devices operably coupled to said LAN and adapted to set user-defined recording cues for choosing said portions of said multimedia conference for playback, wherein setting user-defined recording cues includes training the multimedia server to recognize said recording cues prior to a multimedia conference and automatically recognize participant invocation of a recording cue while a conference is ongoing; and indexing said portions according to user-defined categories.
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7. A telecommunications system, comprising: a local area network (LAN); a multimedia server operably coupled to said network, said multimedia server adapted to manage a multimedia conference and including a memory for storing selectable portions of said multimedia conference; one or more client devices operably coupled to said LAN and adapted to set user-defined recording cues for choosing said portions of said multimedia conference for playback, wherein setting user-defined recording cues includes training the multimedia server to recognize said recording cues prior to a multimedia conference and automatically recognize participant invocation of a recording cue while a conference is ongoing; and indexing said portions according to user-defined categories. 9. A telecommunications system in accordance with claim 7 , wherein said one or more client devices are adapted to set probabilities of recognition of said recording cues.
| 0.506039 |
1. A method for entering a street name to determine an address of a destination for a navigation system, comprising the following steps of: displaying a screen for searching a street name, the screen including a street name input field for accepting a user's input of characters either by a full name or a base name of a street; distinguishing a non-base name element from a base name of a street name in the input character and displaying the non-base name element by a selected method on the screen; comparing the base name detected from the characters input by the user with entries in a base name database that stores base names of streets; retrieving base names from the base name database that match the base name detected from the characters input by the user and displaying a list of the retrieved base names; repeating the above steps of comparing and retrieving the base names every time when additional information is supplied by the user; and retrieving full names of streets from a full name database that stores full names of streets to determine a correct address of the destination.
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1. A method for entering a street name to determine an address of a destination for a navigation system, comprising the following steps of: displaying a screen for searching a street name, the screen including a street name input field for accepting a user's input of characters either by a full name or a base name of a street; distinguishing a non-base name element from a base name of a street name in the input character and displaying the non-base name element by a selected method on the screen; comparing the base name detected from the characters input by the user with entries in a base name database that stores base names of streets; retrieving base names from the base name database that match the base name detected from the characters input by the user and displaying a list of the retrieved base names; repeating the above steps of comparing and retrieving the base names every time when additional information is supplied by the user; and retrieving full names of streets from a full name database that stores full names of streets to determine a correct address of the destination. 3. A method for entering a street name as defined in claim 1 , wherein said step of displaying the non-base name element in the input characters by a selected method includes a step of changing a size or a shape of the non-base name element from that of the base name or adding a crossing-out bar on the non-base name element.
| 0.609785 |
1. A system for storing documents in a repository, comprising: a repository; an interface processor for receiving and storing document data representing a first document and an associated document identifier in said repository; and a document processor for automatically parsing and processing the received document data to identify and store data in said repository indicating: (a) internal document structure and characteristics, and (b) external document relationships comprising data indicating one or more functional types of content inter-relationship between said first document and one or more external documents different to said first document and affecting content of said first document, said internal document structure and characteristics comprising a compilation of searchable keywords and key values, said external document relationships comprising an association or hierarchical relationship between said first document and the one or more different external documents.
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1. A system for storing documents in a repository, comprising: a repository; an interface processor for receiving and storing document data representing a first document and an associated document identifier in said repository; and a document processor for automatically parsing and processing the received document data to identify and store data in said repository indicating: (a) internal document structure and characteristics, and (b) external document relationships comprising data indicating one or more functional types of content inter-relationship between said first document and one or more external documents different to said first document and affecting content of said first document, said internal document structure and characteristics comprising a compilation of searchable keywords and key values, said external document relationships comprising an association or hierarchical relationship between said first document and the one or more different external documents. 10. A system according to claim 1 , wherein said document processor, in response to a received query, dynamically generates a virtual table comprising results of the query.
| 0.652661 |
1. A system, comprising: a memory that stores computer-executable instructions; and a processor, communicatively coupled to the memory, that facilitates execution of the computer-executable instructions to at least: output a set of objects and a set of functionalities in response to one or more queries related to design of an object; receive a selection of a first object from the set of objects and a first functionality from the set of functionalities; apply a set of rules to the first object and the first functionality, wherein the set of rules provides object inheritance of the first functionality and the set of rules relate to a company, an industry, a customer or a regulation; bind the first object and the first functionality as a result of the applied set of rules; determine an expected use for the first object; mask an embedded functionality of the first object and a linked functionality for the first object based on the expected use, wherein the masking hides the embedded functionality and the linked functionality from a user; selectively deactivate at least a portion of the set of functionalities bound to the set of objects based on a determination of an employment role and authorization level of a user; receive information indicative of a rating of the set of objects, wherein the rating is associated with a ranking of the set of objects and is output as a result of a query, and wherein the rating is configured to be employed to determine the set of objects deployed for an application; and associate the rating with the set of objects, and store the rating for the set of objects.
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1. A system, comprising: a memory that stores computer-executable instructions; and a processor, communicatively coupled to the memory, that facilitates execution of the computer-executable instructions to at least: output a set of objects and a set of functionalities in response to one or more queries related to design of an object; receive a selection of a first object from the set of objects and a first functionality from the set of functionalities; apply a set of rules to the first object and the first functionality, wherein the set of rules provides object inheritance of the first functionality and the set of rules relate to a company, an industry, a customer or a regulation; bind the first object and the first functionality as a result of the applied set of rules; determine an expected use for the first object; mask an embedded functionality of the first object and a linked functionality for the first object based on the expected use, wherein the masking hides the embedded functionality and the linked functionality from a user; selectively deactivate at least a portion of the set of functionalities bound to the set of objects based on a determination of an employment role and authorization level of a user; receive information indicative of a rating of the set of objects, wherein the rating is associated with a ranking of the set of objects and is output as a result of a query, and wherein the rating is configured to be employed to determine the set of objects deployed for an application; and associate the rating with the set of objects, and store the rating for the set of objects. 17. The system of claim 1 , wherein the instructions are also executable to: receive login information indicating the identification of the user; and determine the role and the authorization level of the user based on the identification of the user, wherein selective deactivation of the at least a portion of the set of functionalities comprises selective deactivation of the first functionality.
| 0.534175 |
11. A computerized apparatus having a processor, the processor being adapted to perform: obtaining a set of test cases, wherein the set of test cases are useful for testing a target system, wherein the set of test cases are stored electronically, wherein each test case of the set of test cases comprises free-text; defining one or more tags, wherein each tag of the one or more tags is associated with a query, wherein the query is configured, when applied, to determine possession of the tag or lack thereof with respect to a test case based on the free-text; applying queries associated with the one or more tags on the set of test cases to determine possession of the of the one or more tags for each test case of the set of test cases; and generating a functional model based on the set of test cases, wherein the functional model comprising for each tag of the one or more tags, a corresponding functional attribute, wherein the functional model comprising for each test case of the set of test cases, a coverage task, wherein a value of a functional attribute in a coverage task is indicative of possession of the corresponding tag by a corresponding test case.
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11. A computerized apparatus having a processor, the processor being adapted to perform: obtaining a set of test cases, wherein the set of test cases are useful for testing a target system, wherein the set of test cases are stored electronically, wherein each test case of the set of test cases comprises free-text; defining one or more tags, wherein each tag of the one or more tags is associated with a query, wherein the query is configured, when applied, to determine possession of the tag or lack thereof with respect to a test case based on the free-text; applying queries associated with the one or more tags on the set of test cases to determine possession of the of the one or more tags for each test case of the set of test cases; and generating a functional model based on the set of test cases, wherein the functional model comprising for each tag of the one or more tags, a corresponding functional attribute, wherein the functional model comprising for each test case of the set of test cases, a coverage task, wherein a value of a functional attribute in a coverage task is indicative of possession of the corresponding tag by a corresponding test case. 15. The computerized apparatus of claim 11 , wherein said processor is further adapted to provide the functional model to a user to be verified and completed manually, whereby the functional model is defined in a semi-automatic manner.
| 0.570064 |
7. A computer-implemented method comprising: using a processor to provide a web page from a first source; providing a web browser readable code component from a second source different from the first source, the web browser readable code component including dynamically selectable characteristics, the web browser readable code component being useable with a plurality of different web browsers provided by a plurality of different web browser providers; combining the web browser readable code component into the web page; serving the combined web page to a user system; and changing content of a portion of the web page upon execution of the web browser readable code component at the user system without altering the remainder of the web page.
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7. A computer-implemented method comprising: using a processor to provide a web page from a first source; providing a web browser readable code component from a second source different from the first source, the web browser readable code component including dynamically selectable characteristics, the web browser readable code component being useable with a plurality of different web browsers provided by a plurality of different web browser providers; combining the web browser readable code component into the web page; serving the combined web page to a user system; and changing content of a portion of the web page upon execution of the web browser readable code component at the user system without altering the remainder of the web page. 9. The method as claimed in claim 7 wherein the content of the portion of the web page changed upon execution of the web browser readable code component includes an image.
| 0.660401 |
10. A method of distributed rules processing, the method comprising: coupling a server digital data processor to a rules base that stores a plurality of rules that define an application, wherein the server digital data processor operates on a cloud platform, defining an integration link for communication of one or more data between the application and a tenant legacy system during execution of the application, wherein at least one integration rule among the plurality of rules defines the integration link, and wherein the tenant legacy system comprises at least one of a database and a web service that is communicatively coupled to the server digital data processor, facilitating the communication between the tenant legacy system and the application, via one or more coordination modules associated with a respective one of the server digital data processor and the tenant legacy system, in accordance with the integration rule and other tenant legacy system information accessible to the server digital data processor, and simulating a tenant data center environment such that the one or more coordination modules and the tenant legacy system information accessible to the server digital data processor obviate a need to reconfigure the integration rule, so as to maintain the integration link regardless of execution of the application on the server digital data processor or a tenant digital data processor, wherein the tenant legacy system is directly accessible to the tenant digital processor without a firewall preventing such access, and wherein the firewall is coupled to the one or more networks and interrupts the integration link between the application and the tenant legacy system, absent intervention of the one or more coordination modules and the other tenant legacy system information accessible to the server digital data processor.
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10. A method of distributed rules processing, the method comprising: coupling a server digital data processor to a rules base that stores a plurality of rules that define an application, wherein the server digital data processor operates on a cloud platform, defining an integration link for communication of one or more data between the application and a tenant legacy system during execution of the application, wherein at least one integration rule among the plurality of rules defines the integration link, and wherein the tenant legacy system comprises at least one of a database and a web service that is communicatively coupled to the server digital data processor, facilitating the communication between the tenant legacy system and the application, via one or more coordination modules associated with a respective one of the server digital data processor and the tenant legacy system, in accordance with the integration rule and other tenant legacy system information accessible to the server digital data processor, and simulating a tenant data center environment such that the one or more coordination modules and the tenant legacy system information accessible to the server digital data processor obviate a need to reconfigure the integration rule, so as to maintain the integration link regardless of execution of the application on the server digital data processor or a tenant digital data processor, wherein the tenant legacy system is directly accessible to the tenant digital processor without a firewall preventing such access, and wherein the firewall is coupled to the one or more networks and interrupts the integration link between the application and the tenant legacy system, absent intervention of the one or more coordination modules and the other tenant legacy system information accessible to the server digital data processor. 17. The method of claim 10 , further comprising transmitting the one or more coordination modules from the server digital data processor to the tenant digital data processor, in response to a request to access one or more resources available to the server digital data processor.
| 0.53131 |
8. A method, comprising: determining one or more categories that correspond to a plurality of queries; sorting, using one or more processors, the plurality of queries into one or more groups based at least in part on the determined one or more categories of the plurality of queries; segmenting queries that correspond to each of the one or more groups into a first plurality of phrases, wherein each phrase includes one or more words; determining occurrence probabilities for the first plurality of phrases, the determined occurrence probabilities being computed based at least in part on a number of times a phrase occurs in a corresponding group and a number of times the phrase occurs across the one or more groups; determining word information entropies for the first plurality of phrases based at least in part on the determined occurrence probabilities, wherein a word information entropy relates to a degree of uncertainty for a corresponding phrase used in searching; performing a first search using a subsequent query, wherein the subsequent query includes a second plurality of phrases: determining that one or more search results found for the subsequent query do not meet a predetermined rule associated with search results being close matches to the subsequent query; and in response to the determination that the one or more search results returned for the subsequent query do not meet the predetermined rule associated with search results being close matches to the subsequent query; determining a first phrase of the second plurality of phrases of the subsequent query that is associated with a corresponding word information entropy that is less than a threshold value; determining a second phrase of the second plurality of phrases of the subsequent query that is associated with a second corresponding word information entropy that is equal to or greater than the threshold value; generating a new query that includes the first phrase and excludes the second phrase; and performing a second search using the new query.
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8. A method, comprising: determining one or more categories that correspond to a plurality of queries; sorting, using one or more processors, the plurality of queries into one or more groups based at least in part on the determined one or more categories of the plurality of queries; segmenting queries that correspond to each of the one or more groups into a first plurality of phrases, wherein each phrase includes one or more words; determining occurrence probabilities for the first plurality of phrases, the determined occurrence probabilities being computed based at least in part on a number of times a phrase occurs in a corresponding group and a number of times the phrase occurs across the one or more groups; determining word information entropies for the first plurality of phrases based at least in part on the determined occurrence probabilities, wherein a word information entropy relates to a degree of uncertainty for a corresponding phrase used in searching; performing a first search using a subsequent query, wherein the subsequent query includes a second plurality of phrases: determining that one or more search results found for the subsequent query do not meet a predetermined rule associated with search results being close matches to the subsequent query; and in response to the determination that the one or more search results returned for the subsequent query do not meet the predetermined rule associated with search results being close matches to the subsequent query; determining a first phrase of the second plurality of phrases of the subsequent query that is associated with a corresponding word information entropy that is less than a threshold value; determining a second phrase of the second plurality of phrases of the subsequent query that is associated with a second corresponding word information entropy that is equal to or greater than the threshold value; generating a new query that includes the first phrase and excludes the second phrase; and performing a second search using the new query. 12. The method of claim 8 , wherein determining occurrence probabilities for the first plurality of phrases includes determining an occurrence probability of a phrase of a group from the one or more groups, wherein the occurrence probability of the phrase is determined based at least in part on dividing a number of times the phrase occurs in the group by a number of times that the phrase occurs across the one or more groups.
| 0.607143 |
1. A method for creating a flexible structure description, the method comprising: receiving an image of a document of a particular document type that contains a table; receiving an entry describing an item in the table; searching for title elements based upon the entry; detecting data fields and anchor elements for the entry; generating, using a processor, a flexible structure description for the particular document type that includes a set of search elements for each data field in the image of the document and the title elements; matching the flexible structure description against the image; and extracting data from the image based upon the matching of the flexible structure description against the image.
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1. A method for creating a flexible structure description, the method comprising: receiving an image of a document of a particular document type that contains a table; receiving an entry describing an item in the table; searching for title elements based upon the entry; detecting data fields and anchor elements for the entry; generating, using a processor, a flexible structure description for the particular document type that includes a set of search elements for each data field in the image of the document and the title elements; matching the flexible structure description against the image; and extracting data from the image based upon the matching of the flexible structure description against the image. 7. The method of claim 1 , wherein the entry corresponds to a row of the table that spans multiple lines of the document.
| 0.847118 |
14. The system of claim 1 , wherein the DCF comprises plural elements and wherein at least a portion of the elements is lockable to prevent extraction from the DCF.
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14. The system of claim 1 , wherein the DCF comprises plural elements and wherein at least a portion of the elements is lockable to prevent extraction from the DCF. 15. The system of claim 14 , wherein at least a portion of the elements in the DCF is digitally signed.
| 0.958928 |
20. A non-transitory computer readable medium comprising computer executable instructions for retrieving items stored in memory, said computer readable medium comprising instructions for: obtaining zero or more characters as a search input; examining said search input and traversing a tree built from one or more items each having at least one integer associated therewith, each integer representing a component of a respective item and having been generated using a first value indicative of a location where said item can be found in a memory, a second value indicative of a bias level for said item, a third value indicative of an offset within said item where said component begins, and a fourth value indicative of a length of said component within said item to enable said component to be found; upon reaching a terminus in said tree according to said zero or more characters, returning all integers stored at one or more leaf nodes beneath said terminus in said tree; for each integer, determining from said integer, said first value indicative of said location and said second value indicative of said bias level, accessing said item in said memory at said location, determining said third and fourth values, finding said component in said item using said third value, extracting said component according to said fourth value, and returning said component and its bias level for a list of search results; sorting said list of search results using bias levels from said at least one integer; and providing said list of search results.
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20. A non-transitory computer readable medium comprising computer executable instructions for retrieving items stored in memory, said computer readable medium comprising instructions for: obtaining zero or more characters as a search input; examining said search input and traversing a tree built from one or more items each having at least one integer associated therewith, each integer representing a component of a respective item and having been generated using a first value indicative of a location where said item can be found in a memory, a second value indicative of a bias level for said item, a third value indicative of an offset within said item where said component begins, and a fourth value indicative of a length of said component within said item to enable said component to be found; upon reaching a terminus in said tree according to said zero or more characters, returning all integers stored at one or more leaf nodes beneath said terminus in said tree; for each integer, determining from said integer, said first value indicative of said location and said second value indicative of said bias level, accessing said item in said memory at said location, determining said third and fourth values, finding said component in said item using said third value, extracting said component according to said fourth value, and returning said component and its bias level for a list of search results; sorting said list of search results using bias levels from said at least one integer; and providing said list of search results. 24. The non-transitory computer readable medium according to claim 20 , wherein said memory is located in a mobile device.
| 0.525878 |
27. The apparatus of claim 25 , wherein the word alternatives comprise a plurality of data segments, and wherein the analysis controller is further operable to analyze the data segments for which an indication of a segment match is caused to be stored.
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27. The apparatus of claim 25 , wherein the word alternatives comprise a plurality of data segments, and wherein the analysis controller is further operable to analyze the data segments for which an indication of a segment match is caused to be stored. 28. The apparatus of claim 27 , wherein each data segment comprises a conversation, and further comprising a playback controller operable to enable a user to listen to a recording of one or more of the conversations.
| 0.930423 |
7. A method of creating a language model, the method comprising: using a processor to perform acts comprising: analyzing text in a set of documents to determine a set of probabilities associated with N-grams observed in said set of documents; calculating a first quantity that represents how well a first statistical language model predicts occurrence of said N-grams in said set of documents; calculating a second quantity based on said first quantity; creating a second statistical language model based on said second quantity, said first statistical language model, and said set of probabilities, said second quantity comprising a probability that said first statistical language model correctly predicts occurrence of said N-grams in said set of documents, and said creating of said second statistical language model comprising: applying said second quantity to said first statistical language model; and applying a complement of said second quantity to said set of probabilities.
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7. A method of creating a language model, the method comprising: using a processor to perform acts comprising: analyzing text in a set of documents to determine a set of probabilities associated with N-grams observed in said set of documents; calculating a first quantity that represents how well a first statistical language model predicts occurrence of said N-grams in said set of documents; calculating a second quantity based on said first quantity; creating a second statistical language model based on said second quantity, said first statistical language model, and said set of probabilities, said second quantity comprising a probability that said first statistical language model correctly predicts occurrence of said N-grams in said set of documents, and said creating of said second statistical language model comprising: applying said second quantity to said first statistical language model; and applying a complement of said second quantity to said set of probabilities. 8. The method of claim 7 , wherein M is a number of N-grams in said set of documents, and wherein said calculating of said second quantity comprises calculating a divergence between a probability distribution represented by said first statistical language model and a probability distribution represented by said set of probabilities.
| 0.606255 |
1. A computer-implemented method comprising: automatically selecting, by a computer, from a keyword store a set of one or more target words stored in the keyword store, each respective target word having a word difficulty score based upon one or more skill scores of a learner-record stored in a learner database, wherein the keyword store is configured to store metadata associated with each respective target word, and wherein the metadata associated with each respective target word in the keyword word store indicates the word difficulty score of the respective target word; generating, by the computer, a set of one or more syntactic distractors comprising one or more words having a same root word as the target word and having a grammatical difference; and generating, by the computer, at least one more distractor from a group of: a set of one or more semantic distractors comprising one or more words having a definition that is related to a target word, a set of one or more orthographic distractors comprising one or more words of the plurality of words having an edit distance of each respective word satisfying an edit distance amount setting, wherein the edit distance of the word is a number of changes required to the word to be identical to the target word, and wherein the edit distance amount setting determines the number of changes to the word, and, a set of phonetic distractors comprising one or more homophones of the target word, based upon the one or more skill scores of the learner-record.
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1. A computer-implemented method comprising: automatically selecting, by a computer, from a keyword store a set of one or more target words stored in the keyword store, each respective target word having a word difficulty score based upon one or more skill scores of a learner-record stored in a learner database, wherein the keyword store is configured to store metadata associated with each respective target word, and wherein the metadata associated with each respective target word in the keyword word store indicates the word difficulty score of the respective target word; generating, by the computer, a set of one or more syntactic distractors comprising one or more words having a same root word as the target word and having a grammatical difference; and generating, by the computer, at least one more distractor from a group of: a set of one or more semantic distractors comprising one or more words having a definition that is related to a target word, a set of one or more orthographic distractors comprising one or more words of the plurality of words having an edit distance of each respective word satisfying an edit distance amount setting, wherein the edit distance of the word is a number of changes required to the word to be identical to the target word, and wherein the edit distance amount setting determines the number of changes to the word, and, a set of phonetic distractors comprising one or more homophones of the target word, based upon the one or more skill scores of the learner-record. 8. The computer-implemented method of claim 1 , further comprising: identifying, by a computer, in a dictionary source, one or more antonyms of the target word, wherein the set of semantic distractors comprises at least one word having an antonymous definition related to the target word.
| 0.5756 |
1. A system to optimize exchange of data used for third-party content selection, comprising: a data processing system having a keyword selection component, a keyword performance component, and a historic online activity database: the keyword selection component identifies, based on data stored in the historic online activity database, a cluster of client devices that previously performed a plurality of online activities of an online activity type in relation to a product or service context; the keyword selection component determines, based on the data stored in the historic online activity database, from a plurality of keywords, a subset of keywords associated with the plurality of online activities of the online activity type that the cluster of client devices performed in relation to the product or service context; the keyword performance component determines a performance metric of the subset of keywords based on the plurality of online activities of the online activity type that the cluster of client devices performed in relation to the product or service context; and the keyword selection component transmits, to a computing device of a third-party content provider, the subset of keywords and the performance metric; wherein a parameter value determined for a first keyword of the subset of keywords based on the performance metric is used to select a content item of the third-party content provider associated with the product or service context responsive to a request for third-party content, the request for third-party content indicative of the first keyword, the selected content item configured for display on a client device.
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1. A system to optimize exchange of data used for third-party content selection, comprising: a data processing system having a keyword selection component, a keyword performance component, and a historic online activity database: the keyword selection component identifies, based on data stored in the historic online activity database, a cluster of client devices that previously performed a plurality of online activities of an online activity type in relation to a product or service context; the keyword selection component determines, based on the data stored in the historic online activity database, from a plurality of keywords, a subset of keywords associated with the plurality of online activities of the online activity type that the cluster of client devices performed in relation to the product or service context; the keyword performance component determines a performance metric of the subset of keywords based on the plurality of online activities of the online activity type that the cluster of client devices performed in relation to the product or service context; and the keyword selection component transmits, to a computing device of a third-party content provider, the subset of keywords and the performance metric; wherein a parameter value determined for a first keyword of the subset of keywords based on the performance metric is used to select a content item of the third-party content provider associated with the product or service context responsive to a request for third-party content, the request for third-party content indicative of the first keyword, the selected content item configured for display on a client device. 10. The system of claim 1 comprising the keyword selection component configured to: identify one or more other keywords of the plurality of keywords having similar attributes as the subset of keywords; and update the subset of keywords to further include the one or more other keywords, the keyword performance component configured to determine the performance metric based on the updated subset of keywords.
| 0.544796 |
14. A computer program product comprising: a non-transitory computer-readable medium comprising: a first set of codes for causing a computer to receive a plurality of first inputs, wherein each of the first inputs define a search term associated with a case in the electronic discovery system; a second set of codes for causing the computer to store, in a case profile, the search terms as a search term set; a third set of codes for causing a computer to apply the search term set to a portion of a corpus of electronic data associated with the case to determine, in the portion of the corpus of electronic data, (1) an overall quantity of search term hits, (2) a quantity of search term hits for each search term in the search term set, (3) an overall quantity of search term hit counts per data type and (4) a quantity of search term hits for each search term in the search term set per data type, wherein the data types include electronic mail data and electronic file data; a fourth set of codes for causing a computer to predict, for an entirety of the corpus of electronic data based on results of applying the search term set to the portion of electronic data, a volume of the corpus of electronic required to be reviewed; a fifth set of codes for causing a computer to receive one or more second inputs, wherein each of the second inputs modify the search term set based at least on the predicted volume of the corpus of electronic data required to be reviewed; a sixth set of codes for causing a computer to store, in the case profile, the modifications to the search term set including modification tracking data, wherein the modification tracking data includes type of modification, details of the modification, creator of the modification and date of modification type of search term modification, details of the search term modification, originator of the search term modification and date of the search term modification and wherein type of search term modification includes one of adding a search term to the search term set, deleting a search term from the search term set or altering a search term in the search term set; a seventh set of codes for causing a computer to receive a third input, wherein the third input finalizes the search term set; and an eighth set of codes for causing a computer to store, in the case profile, application tracking data associated with applying the search term set to the portion of the electronic data, wherein the application tracking data includes an electronic data identifier, the overall quantity of search term hits within the portion of the corpus of electronic data, the quantity of search term hits per each search term in the search term set within the portion of the corpus of electronic data, and a date for applying the search term set to the portion of the corpus of electronic data.
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14. A computer program product comprising: a non-transitory computer-readable medium comprising: a first set of codes for causing a computer to receive a plurality of first inputs, wherein each of the first inputs define a search term associated with a case in the electronic discovery system; a second set of codes for causing the computer to store, in a case profile, the search terms as a search term set; a third set of codes for causing a computer to apply the search term set to a portion of a corpus of electronic data associated with the case to determine, in the portion of the corpus of electronic data, (1) an overall quantity of search term hits, (2) a quantity of search term hits for each search term in the search term set, (3) an overall quantity of search term hit counts per data type and (4) a quantity of search term hits for each search term in the search term set per data type, wherein the data types include electronic mail data and electronic file data; a fourth set of codes for causing a computer to predict, for an entirety of the corpus of electronic data based on results of applying the search term set to the portion of electronic data, a volume of the corpus of electronic required to be reviewed; a fifth set of codes for causing a computer to receive one or more second inputs, wherein each of the second inputs modify the search term set based at least on the predicted volume of the corpus of electronic data required to be reviewed; a sixth set of codes for causing a computer to store, in the case profile, the modifications to the search term set including modification tracking data, wherein the modification tracking data includes type of modification, details of the modification, creator of the modification and date of modification type of search term modification, details of the search term modification, originator of the search term modification and date of the search term modification and wherein type of search term modification includes one of adding a search term to the search term set, deleting a search term from the search term set or altering a search term in the search term set; a seventh set of codes for causing a computer to receive a third input, wherein the third input finalizes the search term set; and an eighth set of codes for causing a computer to store, in the case profile, application tracking data associated with applying the search term set to the portion of the electronic data, wherein the application tracking data includes an electronic data identifier, the overall quantity of search term hits within the portion of the corpus of electronic data, the quantity of search term hits per each search term in the search term set within the portion of the corpus of electronic data, and a date for applying the search term set to the portion of the corpus of electronic data. 15. The computer program product of claim 14 , wherein the third set of codes is further configured to cause the computer to apply the search term set to the portion of the corpus of electronic data associated with one or more custodians associated with the case.
| 0.5 |
8. In an automatic document handling method for recirculating a set of documents sheets seriatim in a page order for copying on a copier imaging system for making precollated copy sheet sets, the improvement for higher speed document circulation for copying at a higher copying rate comprising the steps of: automatically, in a first circulation of the set of documents, separating the set of document sheets into two half-sets of alternate page document sheets and sequentially placing said half-sets respectively in two different document trays; automatically, on the second and subsequent copying circulations of the document set, feeding the document sheets alternately from said two document sheet half-sets in said two document trays, combined in page seriatim order, to be copied at said imaging station at said higher copying rate; and wherein during said second and subsequent, but not the last, copying circulations said document sheets are re-separated into said half-sets after they are copied as they are returned to said two document trays.
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8. In an automatic document handling method for recirculating a set of documents sheets seriatim in a page order for copying on a copier imaging system for making precollated copy sheet sets, the improvement for higher speed document circulation for copying at a higher copying rate comprising the steps of: automatically, in a first circulation of the set of documents, separating the set of document sheets into two half-sets of alternate page document sheets and sequentially placing said half-sets respectively in two different document trays; automatically, on the second and subsequent copying circulations of the document set, feeding the document sheets alternately from said two document sheet half-sets in said two document trays, combined in page seriatim order, to be copied at said imaging station at said higher copying rate; and wherein during said second and subsequent, but not the last, copying circulations said document sheets are re-separated into said half-sets after they are copied as they are returned to said two document trays. 9. The automatic document handling method of claim 8 wherein a sheet is automatically acquired and begins feeding from one said tray simultaneously with the feeding of another sheet out of the other said tray to said imaging station.
| 0.664303 |
1. A method of providing information to one or more users of an enterprise-based social networking computing environment comprising: generating an informational feed that includes enterprise-based system-generated events associated with one or more users of interest of the enterprise-based social networking computing environment based in part on an organizational context of an enterprise to generate the enterprise-based system-generated events; providing a comment to an enterprise-based system-generated event associated with a defined user of interest; updating the informational feed to delineate the comment interleaved with the enterprise-based system-generated events to display comment information as part of the informational feed; and, providing an updated informational feed including the comment information to a tracking user and automatically adding a commenting user associated with the comment to a tracking list of the tracking user without requiring mutual collaboration in order for the commenting user to be included in the tracking list of the tracking user.
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1. A method of providing information to one or more users of an enterprise-based social networking computing environment comprising: generating an informational feed that includes enterprise-based system-generated events associated with one or more users of interest of the enterprise-based social networking computing environment based in part on an organizational context of an enterprise to generate the enterprise-based system-generated events; providing a comment to an enterprise-based system-generated event associated with a defined user of interest; updating the informational feed to delineate the comment interleaved with the enterprise-based system-generated events to display comment information as part of the informational feed; and, providing an updated informational feed including the comment information to a tracking user and automatically adding a commenting user associated with the comment to a tracking list of the tracking user without requiring mutual collaboration in order for the commenting user to be included in the tracking list of the tracking user. 11. The method of claim 1 , further comprising compressing a comment by an associated enterprise-based system-generated event when the comment and associated enterprise-based system-generated event occur within a defined amount of time.
| 0.63002 |
1. A computer-implemented process for use in a computer network that includes at least two computers communicatively coupled to each other, the process comprising the steps of: (a) accepting a first user's request; (b) searching a local knowledge object repository comprising local knowledge each of the local knowledge objects being associated with the first user; (c) searching a central knowledge object repository comprising contributed knowledge objects; (d) returning to the first user a list of links for all matching local and contributed knowledge objects, said matching local and contributed knowledge objects being marked either local or published or listed; (e) allowing access to said matching local and contributed knowledge objects if the first user chooses a knowledge object marked local or published; (f) forwarding the first user's request to a second user and prompting the second user for authorization of access if the first user chooses a knowledge object marked listed from the list, the second user having control of access to the knowledge object marked listed object; (g) returning to the first user the chosen knowledge object marked listed if the second user allows access; (h) notifying the first user that the request is not completed if the second user declines access to the listed knowledge object.
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1. A computer-implemented process for use in a computer network that includes at least two computers communicatively coupled to each other, the process comprising the steps of: (a) accepting a first user's request; (b) searching a local knowledge object repository comprising local knowledge each of the local knowledge objects being associated with the first user; (c) searching a central knowledge object repository comprising contributed knowledge objects; (d) returning to the first user a list of links for all matching local and contributed knowledge objects, said matching local and contributed knowledge objects being marked either local or published or listed; (e) allowing access to said matching local and contributed knowledge objects if the first user chooses a knowledge object marked local or published; (f) forwarding the first user's request to a second user and prompting the second user for authorization of access if the first user chooses a knowledge object marked listed from the list, the second user having control of access to the knowledge object marked listed object; (g) returning to the first user the chosen knowledge object marked listed if the second user allows access; (h) notifying the first user that the request is not completed if the second user declines access to the listed knowledge object. 7. The process of claim 1 , wherein the step (g) further comprises the step of: prompting the second user to publish the chosen listed knowledge object.
| 0.556766 |
30. A computer-implemented method of preparing a set of documents to support information extraction, the method comprising: defining a set of concept categories, said concept categories including at least one of person, company, and geographical location; defining a set of dyadic relations between concepts, said relations including at least one of affiliation, agent, location, and object; defining a set of rules that allow extraction of relations between concepts, said set of rules including a set of category-specific syntactic constructs and a set of lexical constructs that imply a particular relation; receiving a corpus containing documents; parsing the documents to identify concepts by determining phrase boundaries, determining parts of speech, identifying numeric concepts, identifying phrasal verbs, identifying idioms, and identifying proper names in the documents; extracting, by applying the set of rules to the parsed documents, concept-relation-concept triples, referred to as CRCs, from the parsed documents; and incorporating the CRCs into a data organization.
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30. A computer-implemented method of preparing a set of documents to support information extraction, the method comprising: defining a set of concept categories, said concept categories including at least one of person, company, and geographical location; defining a set of dyadic relations between concepts, said relations including at least one of affiliation, agent, location, and object; defining a set of rules that allow extraction of relations between concepts, said set of rules including a set of category-specific syntactic constructs and a set of lexical constructs that imply a particular relation; receiving a corpus containing documents; parsing the documents to identify concepts by determining phrase boundaries, determining parts of speech, identifying numeric concepts, identifying phrasal verbs, identifying idioms, and identifying proper names in the documents; extracting, by applying the set of rules to the parsed documents, concept-relation-concept triples, referred to as CRCs, from the parsed documents; and incorporating the CRCs into a data organization. 35. The method of claim 30 wherein at least some of said documents are labelled by at least one of the group consisting of source reliability, source credibility, and source reputation.
| 0.5 |
4. The method of claim 3 wherein step (l) includes the steps of: (m) determining, from the stored probabilities, the Markov model having the highest joint probability of producing the ith label of the prototype string and the ith substrings of all the other strings; (n) appending a Markov model in front of the determined Markov model to form an ordered pair of Markov models and computing, based on the stored probabilities, the probability of the ordered pair of Markov models producing the ith label of the prototype string and the each of the ith substrings of the other strings; (o) repeating step (n) for each Markov model in the set as the appended Markov model; (p) appending a Markov model at the end of the selected Markov model to form an ordered pair of Markov models and computing, based on the stored probabilities, the probability of the ordered pair of Markov models producing the i th label of the prototype string and the each of the ith substrings of the other strings; (q) repeating step (p) for each Markov model in the set as the appended Markov model; (r) selecting the ordered pair of the appended Markov model and the selected Markov model that has the highest joint probability of producing the ith label of the prototype string and the each of the ith substrings of the other strings; and (s) performing an alignment process between the selected ordered pair of Markov models and each ith substring, the point in each substring where the two Markov models meet being the consistent point.
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4. The method of claim 3 wherein step (l) includes the steps of: (m) determining, from the stored probabilities, the Markov model having the highest joint probability of producing the ith label of the prototype string and the ith substrings of all the other strings; (n) appending a Markov model in front of the determined Markov model to form an ordered pair of Markov models and computing, based on the stored probabilities, the probability of the ordered pair of Markov models producing the ith label of the prototype string and the each of the ith substrings of the other strings; (o) repeating step (n) for each Markov model in the set as the appended Markov model; (p) appending a Markov model at the end of the selected Markov model to form an ordered pair of Markov models and computing, based on the stored probabilities, the probability of the ordered pair of Markov models producing the i th label of the prototype string and the each of the ith substrings of the other strings; (q) repeating step (p) for each Markov model in the set as the appended Markov model; (r) selecting the ordered pair of the appended Markov model and the selected Markov model that has the highest joint probability of producing the ith label of the prototype string and the each of the ith substrings of the other strings; and (s) performing an alignment process between the selected ordered pair of Markov models and each ith substring, the point in each substring where the two Markov models meet being the consistent point. 5. The method of claim 4 comprising the further steps of: (t) splitting the left portion from the right portion of each ith substring at the respective consistent point thereof; (u) finding the single Markov model P.sub.L having the highest joint probability for the left portions of the ith substrings; (v) finding the two-model sequence, from among all two-model sequences that include the Markov model P.sub.L, which has the highest joint probability of producing the left portions; (w) if the highest probability two-model sequence of step (v) is higher than the probability associated with the single phone P.sub.L, (i) aligning each ith substring against the found two-model sequence and (ii) splitting the found two-model sequence apart at the point of meeting into a resultant left portion and a resultant right portion; and (x) performing steps (t) through (w) with the resultant left portion and the resultant right portion being substituted for the left portion and the right portion respectively.
| 0.69112 |
1. A computer-implemented method, comprising: accessing a first resource belonging to a particular domain; selecting an anchor in the first resource linking to a second resource belonging to the particular domain to which the first resource belongs; identifying particular text content in the first resource that is subordinate to and proximate to the anchor; determining, by one or more computers, whether the second resource includes the particular text content that is subordinate to and proximate to the anchor in the first resource linking to the second resource belonging to the particular domain; in response to determining that the second resource includes the particular text content that is subordinate to and proximate to the anchor in the first resource linking to the second resource belonging to the particular domain, generating a domain template for the particular domain to which the first resource and the second resource belong and that specifies, a location of the particular text content in the second resource; determining one or more resources belonging to the particular domain that have a structure matching the domain template; determining, for each respective resource belonging to the particular domain having a structure matching the domain template, respective text content that is subordinate to the anchor for the respective resource; determining that a particular one of the respective resources is responsive to a search query; and in response to determining that the particular one of the respective resources is responsive to a search query, providing the respective text content that is subordinate to the anchor for the respective resource in response to the search query in a form of a snippet for the particular one of the respective resources in a search results page.
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1. A computer-implemented method, comprising: accessing a first resource belonging to a particular domain; selecting an anchor in the first resource linking to a second resource belonging to the particular domain to which the first resource belongs; identifying particular text content in the first resource that is subordinate to and proximate to the anchor; determining, by one or more computers, whether the second resource includes the particular text content that is subordinate to and proximate to the anchor in the first resource linking to the second resource belonging to the particular domain; in response to determining that the second resource includes the particular text content that is subordinate to and proximate to the anchor in the first resource linking to the second resource belonging to the particular domain, generating a domain template for the particular domain to which the first resource and the second resource belong and that specifies, a location of the particular text content in the second resource; determining one or more resources belonging to the particular domain that have a structure matching the domain template; determining, for each respective resource belonging to the particular domain having a structure matching the domain template, respective text content that is subordinate to the anchor for the respective resource; determining that a particular one of the respective resources is responsive to a search query; and in response to determining that the particular one of the respective resources is responsive to a search query, providing the respective text content that is subordinate to the anchor for the respective resource in response to the search query in a form of a snippet for the particular one of the respective resources in a search results page. 5. The method of claim 1 , wherein determining respective text content for the respective resource comprises generating the snippet from the respective text content for the respective resource.
| 0.640008 |
8. A system comprising: a data store storing targeting criteria for a set of advertisements for one or more campaigns, the targeting criteria for each advertisement in the set including: placement criteria with which presentation of the advertisement is conditioned independent of page keywords for a web property; and target keywords with which presentation of the advertisement is conditioned based on a match existing between one of the target keywords and the page keywords for the web property; and one or more computers configured to interact with the data store, the one or more computers being further configured to perform operations comprising: receiving the placement criteria and the target keywords for theone or more campaigns; receiving a content item request that includes data specifying a requesting web property for which a content item is being requested; identifying, based on the received placement criteria, advertisements that are targeted using placement criteria that identify at least one page of the requesting web property, the identification of the advertisements based on the placement criteria being independent of page keywords of the requesting web property; selecting, as an advertisement that is eligible to be presented with the requesting web property, one of the identified advertisements that, in addition to being targeted using the placement criteria, is further targeted using target keywords that are matched by page keywords for the requesting web property; and providing the selected advertisement in response to the content item request.
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8. A system comprising: a data store storing targeting criteria for a set of advertisements for one or more campaigns, the targeting criteria for each advertisement in the set including: placement criteria with which presentation of the advertisement is conditioned independent of page keywords for a web property; and target keywords with which presentation of the advertisement is conditioned based on a match existing between one of the target keywords and the page keywords for the web property; and one or more computers configured to interact with the data store, the one or more computers being further configured to perform operations comprising: receiving the placement criteria and the target keywords for theone or more campaigns; receiving a content item request that includes data specifying a requesting web property for which a content item is being requested; identifying, based on the received placement criteria, advertisements that are targeted using placement criteria that identify at least one page of the requesting web property, the identification of the advertisements based on the placement criteria being independent of page keywords of the requesting web property; selecting, as an advertisement that is eligible to be presented with the requesting web property, one of the identified advertisements that, in addition to being targeted using the placement criteria, is further targeted using target keywords that are matched by page keywords for the requesting web property; and providing the selected advertisement in response to the content item request. 12. The system of claim 8 , wherein the one or more computers are further configured to perform operations comprising determining a category to which the requesting property has been assigned, the category being determined independent of the page keywords for the requesting web property.
| 0.559178 |
1. A method comprising: identifying boundaries for a phrase in a source sentence by requiring that a source word be aligned with at least one target word in a target sentence in order to form a boundary of a source phrase; identifying boundaries for a phrase in the target sentence based on alignments between words in the source phrase and words in the target sentence; determining if the source phrase and target phrase form a phrase alignment pair by determining if any of the words of the target phrase are aligned with source words outside of the source phrase; if a target word in the target phrase is aligned with a source word outside of the source phrase, a processor excluding a contiguous span of source words as a possible source phrase for phrase alignment pairs without identifying boundaries for a target phrase corresponding to the contiguous span if the contiguous span shares a common boundary with the source phrase, does not include the source word that is outside of the source phrase, and includes all of the words of the source phrase; and storing the source phrase and the target phrase if they form a phrase alignment pair.
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1. A method comprising: identifying boundaries for a phrase in a source sentence by requiring that a source word be aligned with at least one target word in a target sentence in order to form a boundary of a source phrase; identifying boundaries for a phrase in the target sentence based on alignments between words in the source phrase and words in the target sentence; determining if the source phrase and target phrase form a phrase alignment pair by determining if any of the words of the target phrase are aligned with source words outside of the source phrase; if a target word in the target phrase is aligned with a source word outside of the source phrase, a processor excluding a contiguous span of source words as a possible source phrase for phrase alignment pairs without identifying boundaries for a target phrase corresponding to the contiguous span if the contiguous span shares a common boundary with the source phrase, does not include the source word that is outside of the source phrase, and includes all of the words of the source phrase; and storing the source phrase and the target phrase if they form a phrase alignment pair. 4. The method of claim 1 wherein identifying boundaries for a phrase in the target sentence based on alignments between words in the source phrase and words in the target sentence comprises: using a set of alignments for each source word, wherein each set of alignments comprises only the minimum target word position and the maximum target word position aligned with the source word.
| 0.624567 |
13. A system for quality-directed adaptive analytic retraining, comprising: one or more processors operable to receive training example data with which to retrain a machine learning model that has been previously trained; and a memory device operable to store the training example data; one or more of the processors further operable to evaluate the machine learning model at least by running the machine learning model on a processor with the training example data, one or more of the processors further operable to determine a normalized quality measure based on the evaluating, one or more of the processors further operable to determine whether to retrain the machine learning model at least based on the normalized quality measure, and responsive to determining that the machine learning model is to be retrained, one or more of the processors further operable to retrain the machine learning model, wherein responsive to determining that the machine learning model does not need to be retrained, the training example data is accumulated without retraining the machine learning model, wherein one or more of the processors determines whether to retrain the machine learning model at least based on the normalized quality measure, by one or more of: determining whether the quality measure is below a quality threshold, wherein responsive to determining that the quality measure is below the quality threshold, the machine learning model is retrained; or determining whether the quality measure is below a quality threshold, and determining whether a number of available data items comprising at least the training example data meet a specified number of inertia window data items, wherein responsive to determining that the quality measure is below the quality threshold and the number of available data items comprising at least the training example data meet the specified number of inertia window data items, the machine learning model is retrained.
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13. A system for quality-directed adaptive analytic retraining, comprising: one or more processors operable to receive training example data with which to retrain a machine learning model that has been previously trained; and a memory device operable to store the training example data; one or more of the processors further operable to evaluate the machine learning model at least by running the machine learning model on a processor with the training example data, one or more of the processors further operable to determine a normalized quality measure based on the evaluating, one or more of the processors further operable to determine whether to retrain the machine learning model at least based on the normalized quality measure, and responsive to determining that the machine learning model is to be retrained, one or more of the processors further operable to retrain the machine learning model, wherein responsive to determining that the machine learning model does not need to be retrained, the training example data is accumulated without retraining the machine learning model, wherein one or more of the processors determines whether to retrain the machine learning model at least based on the normalized quality measure, by one or more of: determining whether the quality measure is below a quality threshold, wherein responsive to determining that the quality measure is below the quality threshold, the machine learning model is retrained; or determining whether the quality measure is below a quality threshold, and determining whether a number of available data items comprising at least the training example data meet a specified number of inertia window data items, wherein responsive to determining that the quality measure is below the quality threshold and the number of available data items comprising at least the training example data meet the specified number of inertia window data items, the machine learning model is retrained. 14. The system of claim 13 , wherein one or more of the processors is further operable to select a retraining data set by one or more of: selecting all available training data comprising initial training data used to train the machine learning model initially if available and the training example data; selecting training data available since a last retraining of the machine learning model; or selecting a sliding window amount of data of a most recent training data, wherein the machine learning model is retrained with the selected retraining data set.
| 0.527093 |
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. 34. The method of claim 31 , wherein the user interface is a content window that is separate from the source document.
| 0.511846 |
14. A system for connecting information resources in a collaborative work environment, the system comprising: at least one of a processor and a memory providing: a collaborative bot service comprising one or more bots that perform functions comprising: maintaining a topic list of topics found in a plurality of collaboration data sources, the plurality of collaboration data sources comprising a collaborative work environment that comprises a portal facilitating communication between a plurality of users who contribute collaboration information to the collaborative work environment via one or more user interfaces; automatically and autonomously monitoring the collaboration work environment, the monitoring comprising traversing the collaboration information provided within the collaborative work environment via a user interface by the plurality of users; extracting, using a text-mining tool upon detection via the monitoring of new collaboration information contributed by one of the plurality of users in the collaborative work environment for use by at least one other of the plurality of users in the collaborative work environment, an extracted topic of the new collaboration information, the extracted topic comprising at least one of a theme, a question, a problem, and a subject matter of the new collaboration information; identifying an information resource within the plurality of collaboration data sources that is related to the extracted topic, the identifying comprising comparing the extracted topic to the topic list and determining that previously contributed collaboration information available from the information resource has a topic related to the extracted topic; creating a link insertable into a collaborative process, through which the plurality of users can send communications, of the collaborative work environment, the link being to the information resource identified as related to the extracted topic of the new collaboration information contributed by the one of the plurality of users for use by the at least one other of the plurality of users in the collaborative work environment; and inserting the link into the collaborative process through which the plurality of users can send communications and into the user interface in a close proximal relation to the new collaboration information.
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14. A system for connecting information resources in a collaborative work environment, the system comprising: at least one of a processor and a memory providing: a collaborative bot service comprising one or more bots that perform functions comprising: maintaining a topic list of topics found in a plurality of collaboration data sources, the plurality of collaboration data sources comprising a collaborative work environment that comprises a portal facilitating communication between a plurality of users who contribute collaboration information to the collaborative work environment via one or more user interfaces; automatically and autonomously monitoring the collaboration work environment, the monitoring comprising traversing the collaboration information provided within the collaborative work environment via a user interface by the plurality of users; extracting, using a text-mining tool upon detection via the monitoring of new collaboration information contributed by one of the plurality of users in the collaborative work environment for use by at least one other of the plurality of users in the collaborative work environment, an extracted topic of the new collaboration information, the extracted topic comprising at least one of a theme, a question, a problem, and a subject matter of the new collaboration information; identifying an information resource within the plurality of collaboration data sources that is related to the extracted topic, the identifying comprising comparing the extracted topic to the topic list and determining that previously contributed collaboration information available from the information resource has a topic related to the extracted topic; creating a link insertable into a collaborative process, through which the plurality of users can send communications, of the collaborative work environment, the link being to the information resource identified as related to the extracted topic of the new collaboration information contributed by the one of the plurality of users for use by the at least one other of the plurality of users in the collaborative work environment; and inserting the link into the collaborative process through which the plurality of users can send communications and into the user interface in a close proximal relation to the new collaboration information. 15. A system in accordance with claim 14 , further comprising a repository framework providing access to the plurality of collaboration data sources including the collaborative work environment.
| 0.535299 |
1. A method for providing recommendations that take into account users' casual references to certain media assets during conversational communications by isolating a term in the conversational communications and determining relationships to that term through the use of a knowledge graph organized to store relationships between different pieces of information, comprising: receiving, via a user interface, a user communication; analyzing, via processing circuitry, the user communication based on a previously stored template from a database to determine a term of the user communication; transmitting a query based on the term to a knowledge graph having a plurality of nodes representing different pieces of information and a plurality of edges connecting the plurality of nodes representing relationships between the different pieces of information; identifying a first node representing a candidate component that is connected to a second node representing the term based on the knowledge graph; generating for display, via the user interface, a request causing user input directed to confirming whether the term is associated with the candidate component; in response to receiving the user input, modifying a strength of association represented by a weight allocated to an edge connecting the second node representing the term and the first node representing the candidate component in the knowledge graph; and generating a content recommendation associated with the candidate component based on the strength of association.
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1. A method for providing recommendations that take into account users' casual references to certain media assets during conversational communications by isolating a term in the conversational communications and determining relationships to that term through the use of a knowledge graph organized to store relationships between different pieces of information, comprising: receiving, via a user interface, a user communication; analyzing, via processing circuitry, the user communication based on a previously stored template from a database to determine a term of the user communication; transmitting a query based on the term to a knowledge graph having a plurality of nodes representing different pieces of information and a plurality of edges connecting the plurality of nodes representing relationships between the different pieces of information; identifying a first node representing a candidate component that is connected to a second node representing the term based on the knowledge graph; generating for display, via the user interface, a request causing user input directed to confirming whether the term is associated with the candidate component; in response to receiving the user input, modifying a strength of association represented by a weight allocated to an edge connecting the second node representing the term and the first node representing the candidate component in the knowledge graph; and generating a content recommendation associated with the candidate component based on the strength of association. 8. The method of claim 1 , wherein identifying the candidate component further comprises cross-referencing the term with a plurality of candidate components of the knowledge graph stored in a database.
| 0.864973 |
14. A system comprising one or more computing devices operable to perform operations including: receiving an identification of user group configuration settings for a user group comprising a plurality of users, the user group configuration settings identifying a first plurality of content items to be retrieved from a first plurality of remote content provider servers and to be provided in a user group container document; generating the user group container document based on the user group configuration settings, the user group container document comprising a first plurality of content modules that provide the first plurality of content items from the first plurality of remote content provider servers; sending the user group container document over a public network to each of a plurality of client devices; receiving from the client devices data identifying personal configuration settings for each of the plurality of users in the user group, each of the personal configuration settings specifying a second plurality of content items to be retrieved from a second plurality of remote content provider servers and to be included in personal container documents; generating a first personal container document based on the user group configuration settings and the personal configuration settings for a first user, the container document comprising: one or more of the first plurality of content modules that provide the first plurality of content items from the first plurality of remote content provider servers; and a second plurality of content modules that provide the second plurality of content items from a second plurality of remote content provider servers.
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14. A system comprising one or more computing devices operable to perform operations including: receiving an identification of user group configuration settings for a user group comprising a plurality of users, the user group configuration settings identifying a first plurality of content items to be retrieved from a first plurality of remote content provider servers and to be provided in a user group container document; generating the user group container document based on the user group configuration settings, the user group container document comprising a first plurality of content modules that provide the first plurality of content items from the first plurality of remote content provider servers; sending the user group container document over a public network to each of a plurality of client devices; receiving from the client devices data identifying personal configuration settings for each of the plurality of users in the user group, each of the personal configuration settings specifying a second plurality of content items to be retrieved from a second plurality of remote content provider servers and to be included in personal container documents; generating a first personal container document based on the user group configuration settings and the personal configuration settings for a first user, the container document comprising: one or more of the first plurality of content modules that provide the first plurality of content items from the first plurality of remote content provider servers; and a second plurality of content modules that provide the second plurality of content items from a second plurality of remote content provider servers. 23. The system of claim 14 , the operations further comprising sending the generated first personal container document to a client device over a public network in a secure manner.
| 0.63422 |
20. The article of manufacture of claim 17 , wherein the instructions, when executed, cause the processor to identify a second element corresponding to the first element, link the second element with the first element, and replace the second element with an escape sequence associated with the dynamic element.
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20. The article of manufacture of claim 17 , wherein the instructions, when executed, cause the processor to identify a second element corresponding to the first element, link the second element with the first element, and replace the second element with an escape sequence associated with the dynamic element. 21. The article of manufacture of claim 20 , wherein the instructions, when executed, cause the processor to receive a linking designation to link the first element and the second element.
| 0.870715 |
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