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8,352,269 | 1 | 2 |
1. A computer implemented method comprising: processing, by one or more computers, a first indicium of a plurality of indicia applied by a user over a first portion of words in a document; determining, by the one or more computers, a first voice model to associate with the first portion of words, with the first voice model represented by the first indicium applied by the user over the first portion of words; and generating, by the one or more computers, an audible output corresponding to the words in the first portion of words using the voice model associated with the first portion of words.
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1. A computer implemented method comprising: processing, by one or more computers, a first indicium of a plurality of indicia applied by a user over a first portion of words in a document; determining, by the one or more computers, a first voice model to associate with the first portion of words, with the first voice model represented by the first indicium applied by the user over the first portion of words; and generating, by the one or more computers, an audible output corresponding to the words in the first portion of words using the voice model associated with the first portion of words. 2. The method of claim 1 , further comprising: processing, by the one or more computers, a second indicium in the document to determine a second portion of words in the document, the second portion of words being different from the first portion of words; determining, by the one or more computers, a second, different voice model to associate with the second portion of words based on the second indicia; and generating, by the one or more computers, an audible output corresponding to the words in the second portion of words using the second, different voice model associated with the second portion of words.
| 0.5 |
9,183,289 | 7 | 8 |
7. The method of claim 4 further comprising: comparing security classifications of the selected portion of text to current document security classifications; and updating security classification properties of document metadata when the security classification of the selected portion of text are higher than current document security classification.
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7. The method of claim 4 further comprising: comparing security classifications of the selected portion of text to current document security classifications; and updating security classification properties of document metadata when the security classification of the selected portion of text are higher than current document security classification. 8. The method of claim 7 wherein portions of text of the XML based word processing document may have a lower security classification than the document security classification, the portions of text being identified with portion marking.
| 0.5 |
8,326,627 | 30 | 32 |
30. The navigation device of claim 23 , wherein the dynamic recognition grammar organizes the grammar information according to geographic chunks based on the one or more topological domains associated with the current location associated with the navigation device.
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30. The navigation device of claim 23 , wherein the dynamic recognition grammar organizes the grammar information according to geographic chunks based on the one or more topological domains associated with the current location associated with the navigation device. 32. The navigation device of claim 30 , wherein the geographic chunks include physical proximities that relate to a distance from the current location associated with the navigation device, temporal proximities that relate to a travel time from the current location associated with the navigation device, directional proximities that relate to a directional travel vector from the current location associated with the navigation device, or civil organizational proximities that relate to continents, countries, regions, states, cities, localities, neighborhoods, or communities mapped to the current location associated with the navigation device.
| 0.5 |
9,973,488 | 11 | 16 |
11. A computer-implemented method, comprising: receiving a first request to cause temporary password information to be added to a set of password information associated with a user, the first request being received in response to a login to a multi-tenant computing environment, and the set of password information associated with the user comprising a plurality of instances of password information; receiving a second request for authentication information to be provided to a target component, the second request based at least in part upon the temporary password information; adding the temporary password information to the set of password information, the set of password information including at least password information corresponding to a password known to the user, the temporary password information available for generating a ticket granting ticket (TGT); determining, based at least in part on the second request for authentication information, that the target component to receive the authentication information is not configured to accept the TGT; and generating a response to the second request for authentication information including at least a subset of the set of password information when the target component is determined as not being configured to accept the TGT.
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11. A computer-implemented method, comprising: receiving a first request to cause temporary password information to be added to a set of password information associated with a user, the first request being received in response to a login to a multi-tenant computing environment, and the set of password information associated with the user comprising a plurality of instances of password information; receiving a second request for authentication information to be provided to a target component, the second request based at least in part upon the temporary password information; adding the temporary password information to the set of password information, the set of password information including at least password information corresponding to a password known to the user, the temporary password information available for generating a ticket granting ticket (TGT); determining, based at least in part on the second request for authentication information, that the target component to receive the authentication information is not configured to accept the TGT; and generating a response to the second request for authentication information including at least a subset of the set of password information when the target component is determined as not being configured to accept the TGT. 16. The computer-implemented method of claim 11 , wherein in at least one instance of password information of the set of password information is associated with one or more usage constraints.
| 0.772619 |
10,133,736 | 2 | 3 |
2. The system of claim 1 , wherein the sentence parsing further comprises the analogy manager to: identify grammatical sub-components of the segments; identify grammatical sub-components of the analogy phrase; and match at least one segment grammatical sob-component corresponding to at least one analogy phrase grammatical sub-component.
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2. The system of claim 1 , wherein the sentence parsing further comprises the analogy manager to: identify grammatical sub-components of the segments; identify grammatical sub-components of the analogy phrase; and match at least one segment grammatical sob-component corresponding to at least one analogy phrase grammatical sub-component. 3. The system of claim 2 , further comprising the analogy manager to assign the match to the replaced anaphora in the created sentence structure.
| 0.5 |
8,161,112 | 17 | 18 |
17. The computer program product of claim 16 further comprising computer readable program code configured to classify a structural element of the structured document according to a presentation attribute.
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17. The computer program product of claim 16 further comprising computer readable program code configured to classify a structural element of the structured document according to a presentation attribute. 18. The computer program product of claim 17 wherein the computer readable program code configured to classify a structural element comprises: computer readable program code configured to identify a presentation attribute for the structural element; computer readable program code configured to identify a classification identifier in dependence upon the presentation attribute; and computer readable program code configured to insert the classification identifier in association with the structural element in the structured document.
| 0.5 |
7,953,694 | 1 | 5 |
1. A computer-implemented method for specifying on-line analytical processing multidimensional calculations, comprising: accessing, using a computer including a processor, measures that include symmetric and asymmetric measures, wherein each of the symmetric measures have a single aggregation, and wherein each of the asymmetric measures have multiple aggregations, wherein a measure is defined by one or more structured query language expressions and wherein the one or more structured query language expressions are used as input to an aggregation of the measure; selecting each of the symmetric and asymmetric measures one at a time; and for the selected one of the symmetric and asymmetric measures, determining whether the selected measure is compatible with previously selected measures, wherein compatible measures have a same specification of aggregation order for dimensions that the measures reference; in response to determining that the selected measure is compatible, selecting another of the symmetric and asymmetric measures; and in response to determining that the selected measure is not compatible, determining whether one or more measures of the symmetric and asymmetric measures can be rewritten so that the selected measure is compatible with the previously selected measures; in response to determining that the one or more measures of the symmetric and asymmetric measures can be rewritten, rewriting the one or more measures of the symmetric and asymmetric measures; and in response to determining that the one or more measures of the symmetric and asymmetric measures cannot be rewritten, generating a first structured query language statement for the symmetric measures; generating a second structured query language statement for the asymmetric measures; and combining the first structured query language statement and the second structured query language statement for the symmetric and asymmetric measures into a single structured query language statement.
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1. A computer-implemented method for specifying on-line analytical processing multidimensional calculations, comprising: accessing, using a computer including a processor, measures that include symmetric and asymmetric measures, wherein each of the symmetric measures have a single aggregation, and wherein each of the asymmetric measures have multiple aggregations, wherein a measure is defined by one or more structured query language expressions and wherein the one or more structured query language expressions are used as input to an aggregation of the measure; selecting each of the symmetric and asymmetric measures one at a time; and for the selected one of the symmetric and asymmetric measures, determining whether the selected measure is compatible with previously selected measures, wherein compatible measures have a same specification of aggregation order for dimensions that the measures reference; in response to determining that the selected measure is compatible, selecting another of the symmetric and asymmetric measures; and in response to determining that the selected measure is not compatible, determining whether one or more measures of the symmetric and asymmetric measures can be rewritten so that the selected measure is compatible with the previously selected measures; in response to determining that the one or more measures of the symmetric and asymmetric measures can be rewritten, rewriting the one or more measures of the symmetric and asymmetric measures; and in response to determining that the one or more measures of the symmetric and asymmetric measures cannot be rewritten, generating a first structured query language statement for the symmetric measures; generating a second structured query language statement for the asymmetric measures; and combining the first structured query language statement and the second structured query language statement for the symmetric and asymmetric measures into a single structured query language statement. 5. The method of claim 1 , further comprising: generating a new statement for retrieving multidimensional information, wherein the new statement is a structured query language statement and wherein the structured query language statement is generated based on the one or more aggregations in each of the measures.
| 0.510938 |
8,296,729 | 1 | 3 |
1. A system comprising: a back-end computing system comprising a library that contains objects for use with an advanced business application programming (ABAP) language; and a front-end computing system that executes, using a processor, an Eclipse development environment, the Eclipse development environment comprising a plug-in, the plug-in enabling the Eclipse development environment to recognize the ABAP language and to access the library.
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1. A system comprising: a back-end computing system comprising a library that contains objects for use with an advanced business application programming (ABAP) language; and a front-end computing system that executes, using a processor, an Eclipse development environment, the Eclipse development environment comprising a plug-in, the plug-in enabling the Eclipse development environment to recognize the ABAP language and to access the library. 3. The system of claim 1 , wherein the plug-in performs autocompletion for the ABAP language in the Eclipse development environment.
| 0.635359 |
8,635,561 | 13 | 14 |
13. The method of claim 12 , the expanded view for the second snippet output in place of the expanded view for the first snippet.
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13. The method of claim 12 , the expanded view for the second snippet output in place of the expanded view for the first snippet. 14. The method of claim 13 , the received plurality of snippets including a third snippet based on a third email, the method further comprising: outputting, for simultaneous display with the expanded view of the second snippet, the condensed view for the snippet of the third email.
| 0.5 |
9,786,299 | 3 | 4 |
3. The apparatus of claim 1 , the at least one fact or profile input comprising at least one user configuration parameter directly input by the user to the mobile communications device.
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3. The apparatus of claim 1 , the at least one fact or profile input comprising at least one user configuration parameter directly input by the user to the mobile communications device. 4. The apparatus of claim 3 , the at least one user configuration parameter comprising at least one of hobbies, interests, personality traits, favorite movies, favorite sports, and favorite types of cuisine.
| 0.743812 |
8,433,712 | 11 | 12 |
11. A non-transitory computer readable storage medium for improving link scores in an enterprise search system, comprising instructions, said instructions which when executed, cause one or more processors to perform: crawling one or more documents in an enterprise system; storing a document host corresponding to each crawled document of the one or more documents identifying a set of links included in said each crawled document, wherein a link of the set of links is included in said each crawled document and points to a second document; storing source host information in association with each link included in said each crawled document, wherein the source host is the same host as the document host corresponding to said each crawled document; determining, using a processor operatively coupled with a memory, a link score for the one or more documents in the enterprise system, further comprising: for a particular document of the one or more documents, identifying a set of incoming links, wherein an incoming link of the set of incoming links points to the particular document; counting a number of incoming links that are not same host links; wherein a same host link has an associated source host that is the same as the document host associated with the particular document; determining a ratio of a first number of incoming links to a second number of incoming links, wherein the first number of incoming links is a number of incoming links that are not same host links, and the second number of incoming links is a total number of incoming links including same host links; pushing the link score into the database table, wherein the link score is associated with the particular document; receiving a search query string from a user; and querying the database table with the search query string and a requested link score such that documents including the query string and associated with the requested link score are returned.
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11. A non-transitory computer readable storage medium for improving link scores in an enterprise search system, comprising instructions, said instructions which when executed, cause one or more processors to perform: crawling one or more documents in an enterprise system; storing a document host corresponding to each crawled document of the one or more documents identifying a set of links included in said each crawled document, wherein a link of the set of links is included in said each crawled document and points to a second document; storing source host information in association with each link included in said each crawled document, wherein the source host is the same host as the document host corresponding to said each crawled document; determining, using a processor operatively coupled with a memory, a link score for the one or more documents in the enterprise system, further comprising: for a particular document of the one or more documents, identifying a set of incoming links, wherein an incoming link of the set of incoming links points to the particular document; counting a number of incoming links that are not same host links; wherein a same host link has an associated source host that is the same as the document host associated with the particular document; determining a ratio of a first number of incoming links to a second number of incoming links, wherein the first number of incoming links is a number of incoming links that are not same host links, and the second number of incoming links is a total number of incoming links including same host links; pushing the link score into the database table, wherein the link score is associated with the particular document; receiving a search query string from a user; and querying the database table with the search query string and a requested link score such that documents including the query string and associated with the requested link score are returned. 12. The non-transitory computer-readable storage medium of claim 11 , further comprising instructions, which when executed, cause one or more processors to perform determining the link score based on the ratio.
| 0.5 |
7,509,406 | 33 | 39 |
33. The method of claim 28 , wherein saving the session metrics comprises saving at least one of the following: the date when the user requested access to the TS session; the time when the user requested access to the TS session; a time at which the TS account was provisioned; the time at which the hosted application is launched; the difference in time between the time the user requested access to the TS session and the time at which the hosted application is launched; a time the TS session is disconnected; the difference in time between the time the TS session is disconnected and the time when the user requested access to the TS session; the language associated with the TS account located; an identifier of the asset where the TS account is located; an IP address from which the user accessed the TS session; and a name of a terminal server utilized for the TS session.
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33. The method of claim 28 , wherein saving the session metrics comprises saving at least one of the following: the date when the user requested access to the TS session; the time when the user requested access to the TS session; a time at which the TS account was provisioned; the time at which the hosted application is launched; the difference in time between the time the user requested access to the TS session and the time at which the hosted application is launched; a time the TS session is disconnected; the difference in time between the time the TS session is disconnected and the time when the user requested access to the TS session; the language associated with the TS account located; an identifier of the asset where the TS account is located; an IP address from which the user accessed the TS session; and a name of a terminal server utilized for the TS session. 39. The computer-readable storage medium program product of claim 33 , wherein the control logic further comprises computer readable program code means for causing the computer to retrieve dialog information based on the language associated with the TS account located and render the dialog information to the user in response to the user attempting to use at least one of the designated features restricted and the designated functionality restricted.
| 0.5 |
8,336,021 | 11 | 13 |
11. At a computer system including one or more processors and system memory, a method for determining if a reference that is to be created or modified is a member of a set, the method comprising: an act of receiving a resource request corresponding to a specified resource; an act of accessing one or more membership conditions for the set, the one or more membership conditions having been previously translated from a set definition defining the set, matching at least one of the one or more membership conditions being an indication of membership in the set, each membership condition including one or more membership condition statements that are to be satisfied for a resource to match the membership condition, each membership condition statement including: a referent field, an attribute field, an operator field, and a value field that collectively represent the membership condition statement, each of the referent field, attribute field, operator field, and value field being defined within the membership condition grammar as: <Referent>::=<Referent Reference><Attribute>, <Attribute>::=a name of an attribute of a resource identified by an expression to its left, <Operator>::=<Relational Operator>|<Inverted Operator>, and <Value>::=<Literal Value>|<Function Value>|<De-referenced Value>, and further: the attribute field naming an attribute, the operator field indicating a relational operator, the value field representing a value, the referent field indicating a referent, the referent referring either directly to the resource currently being evaluated for membership in the set or to another resource that is related in some way to the resource that is currently being evaluated for membership in the set; for each of the one or more membership condition statements, an act of evaluating the named attribute of the specified resource against the value in the value field in view of the operator in the operator field to determine if the specified resource satisfies the membership condition statement; an act of determining that the specified resource satisfies membership condition statements for at least one of membership conditions based on the evaluations; an act of matching the specified resource to the condition statement as a result of the specified resource satisfying membership condition statements for the at least one of the membership conditions; and an act of including the specified resource as a member of the set in response to the specified resource matching the condition statement.
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11. At a computer system including one or more processors and system memory, a method for determining if a reference that is to be created or modified is a member of a set, the method comprising: an act of receiving a resource request corresponding to a specified resource; an act of accessing one or more membership conditions for the set, the one or more membership conditions having been previously translated from a set definition defining the set, matching at least one of the one or more membership conditions being an indication of membership in the set, each membership condition including one or more membership condition statements that are to be satisfied for a resource to match the membership condition, each membership condition statement including: a referent field, an attribute field, an operator field, and a value field that collectively represent the membership condition statement, each of the referent field, attribute field, operator field, and value field being defined within the membership condition grammar as: <Referent>::=<Referent Reference><Attribute>, <Attribute>::=a name of an attribute of a resource identified by an expression to its left, <Operator>::=<Relational Operator>|<Inverted Operator>, and <Value>::=<Literal Value>|<Function Value>|<De-referenced Value>, and further: the attribute field naming an attribute, the operator field indicating a relational operator, the value field representing a value, the referent field indicating a referent, the referent referring either directly to the resource currently being evaluated for membership in the set or to another resource that is related in some way to the resource that is currently being evaluated for membership in the set; for each of the one or more membership condition statements, an act of evaluating the named attribute of the specified resource against the value in the value field in view of the operator in the operator field to determine if the specified resource satisfies the membership condition statement; an act of determining that the specified resource satisfies membership condition statements for at least one of membership conditions based on the evaluations; an act of matching the specified resource to the condition statement as a result of the specified resource satisfying membership condition statements for the at least one of the membership conditions; and an act of including the specified resource as a member of the set in response to the specified resource matching the condition statement. 13. The method as recited in claim 11 , wherein the act of receiving a resource request corresponding to a specified resource comprises an act of receiving a request to create a resource.
| 0.732092 |
9,798,538 | 1 | 12 |
1. A method of providing supplemental functionalities to an executable program, the method being implemented by a computer system comprising one or more processors executing one or more computer program instructions that, when executed, perform the method, the method comprising: causing an executable program associated with an ontology to be run, wherein the ontology comprises information indicating attributes for a set of applications; obtaining a domain-specific ontology, wherein the domain-specific ontology is within a domain of interest; obtaining an ontology instance of the ontology based on the domain-specific ontology, the ontology instance corresponding to an application of the set of applications that is within the domain of interest; extracting axiom information from the ontology; generating a set of logic rules using the axiom information; computing entailments on the ontology instance using the set of logic rules, wherein the entailments include asserted and inferred class membership of the ontology instance and verify that no axioms indicated in the axiom information are violated; using the ontology instance to generate application metadata for the executable program, wherein at least part of the application metadata is generated based on the set of logic rules, and wherein the application metadata defines one or more functionalities of the application of the set of applications that is within the domain of interest; and providing the application metadata as input to the executable program, wherein the application metadata, at least in part, causes the one or more functionalities of the application to be made available via the executable program.
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1. A method of providing supplemental functionalities to an executable program, the method being implemented by a computer system comprising one or more processors executing one or more computer program instructions that, when executed, perform the method, the method comprising: causing an executable program associated with an ontology to be run, wherein the ontology comprises information indicating attributes for a set of applications; obtaining a domain-specific ontology, wherein the domain-specific ontology is within a domain of interest; obtaining an ontology instance of the ontology based on the domain-specific ontology, the ontology instance corresponding to an application of the set of applications that is within the domain of interest; extracting axiom information from the ontology; generating a set of logic rules using the axiom information; computing entailments on the ontology instance using the set of logic rules, wherein the entailments include asserted and inferred class membership of the ontology instance and verify that no axioms indicated in the axiom information are violated; using the ontology instance to generate application metadata for the executable program, wherein at least part of the application metadata is generated based on the set of logic rules, and wherein the application metadata defines one or more functionalities of the application of the set of applications that is within the domain of interest; and providing the application metadata as input to the executable program, wherein the application metadata, at least in part, causes the one or more functionalities of the application to be made available via the executable program. 12. The method of claim 1 , wherein the ontology does not have a dependency on the domain-specific ontology.
| 0.906574 |
7,729,655 | 1 | 7 |
1. A computer-implemented method for providing individualized essay writing instruction, the method comprising: receiving an essay in an electronic format using a computer; automatically determining with the computer a first value for each sentence in the essay that reflects the probability that the sentence is a member of a discourse element category, wherein the probability is based on the presence of each of a predetermined set of features in the sentence; utilizing the first value to determine with the computer whether each sentence in the essay should be assigned to a discourse element category; identifying with the computer any discourse elements in the essay; if the first values do not indicate the presence of a discourse element in the essay, indicating that the essay lacks sufficient clarity; generating feedback regarding the presence or absence of discourse elements in the essay; and transmitting the feedback for display to a user.
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1. A computer-implemented method for providing individualized essay writing instruction, the method comprising: receiving an essay in an electronic format using a computer; automatically determining with the computer a first value for each sentence in the essay that reflects the probability that the sentence is a member of a discourse element category, wherein the probability is based on the presence of each of a predetermined set of features in the sentence; utilizing the first value to determine with the computer whether each sentence in the essay should be assigned to a discourse element category; identifying with the computer any discourse elements in the essay; if the first values do not indicate the presence of a discourse element in the essay, indicating that the essay lacks sufficient clarity; generating feedback regarding the presence or absence of discourse elements in the essay; and transmitting the feedback for display to a user. 7. The method of claim 1 wherein the predetermined set of features comprises a feature based on a presence or an absence of one or more selected words.
| 0.589674 |
8,346,537 | 10 | 15 |
10. An input method for use with an input apparatus comprising: storing a plurality of multi-word example expressions in an electronic medium, each example expression including at least one editable portion, said example expressions being stored in said electronic medium prior to a current use of said apparatus by a user; electronically selecting at least one of said example expressions from the examples stored in the example storage module to be presented to a user of the input apparatus as a presentation example based on the current use being made of the apparatus as determined by a physical activity association with the current location, but not the language spoken at that location; electronically displaying said at least one presentation example; electronically editing at least the editable portion of the at least one of the displayed presentation examples based on user input; electronically storing words of the one of the example expression before the edit and words thereof after the edit; and exercising the option of selecting between: accepting the unedited presentation example expression for further processing upon a selection of it by the user; or accepting the edited presentation example expression for further processing upon the edit of it by the user.
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10. An input method for use with an input apparatus comprising: storing a plurality of multi-word example expressions in an electronic medium, each example expression including at least one editable portion, said example expressions being stored in said electronic medium prior to a current use of said apparatus by a user; electronically selecting at least one of said example expressions from the examples stored in the example storage module to be presented to a user of the input apparatus as a presentation example based on the current use being made of the apparatus as determined by a physical activity association with the current location, but not the language spoken at that location; electronically displaying said at least one presentation example; electronically editing at least the editable portion of the at least one of the displayed presentation examples based on user input; electronically storing words of the one of the example expression before the edit and words thereof after the edit; and exercising the option of selecting between: accepting the unedited presentation example expression for further processing upon a selection of it by the user; or accepting the edited presentation example expression for further processing upon the edit of it by the user. 15. The method of claim 10 further comprising: identifying when a user partially edits a presentation example; specifying the edited portion; and electronically registering an indication that a wording before editing is associated with a wording after editing.
| 0.738956 |
9,575,960 | 17 | 18 |
17. The system of claim 15 , wherein the instructions when executed further cause the system to: estimate a reading pace associated with the user; and detect a page turn command input by the user, wherein the estimated location is determined based at least in part upon the page turn command and the reading pace.
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17. The system of claim 15 , wherein the instructions when executed further cause the system to: estimate a reading pace associated with the user; and detect a page turn command input by the user, wherein the estimated location is determined based at least in part upon the page turn command and the reading pace. 18. The system of claim 17 , wherein the reading pace associated with the user is estimated based at least in part upon historical data regarding a time it took for the user to turn one or more pages in one or more previously read electronic documents.
| 0.5 |
9,460,079 | 1 | 9 |
1. A method of providing a dictionary service to a user terminal, the method comprising: configuring a first area of a display to receive a keyword as an input and a second area of the display to display a dictionary search result of the keyword when the user terminal is operating in a dictionary mode; switching from the dictionary mode to a translation mode if the keyword input into the first area is greater than or equal to a threshold length, the switching includes reconfiguring a user interface such that the first area of the display extends into a third area of the display; setting the keyword as a source text to translate and display in the third area of the display, if the keyword is greater than or equal to the threshold length; and determining as the dictionary search result a definition of the keyword and displaying, in the second area, the dictionary search result, if the keyword is less than the threshold length.
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1. A method of providing a dictionary service to a user terminal, the method comprising: configuring a first area of a display to receive a keyword as an input and a second area of the display to display a dictionary search result of the keyword when the user terminal is operating in a dictionary mode; switching from the dictionary mode to a translation mode if the keyword input into the first area is greater than or equal to a threshold length, the switching includes reconfiguring a user interface such that the first area of the display extends into a third area of the display; setting the keyword as a source text to translate and display in the third area of the display, if the keyword is greater than or equal to the threshold length; and determining as the dictionary search result a definition of the keyword and displaying, in the second area, the dictionary search result, if the keyword is less than the threshold length. 9. The method of claim 1 , further comprising: receiving a translation of the keyword from the server in response to switching to the translation mode; and displaying the translation on a fourth area of the display distinguished from the third area.
| 0.802067 |
9,785,317 | 10 | 12 |
10. The method of claim 9 , wherein the spatial layout of the displayed graph is updated in response to inputs from the operator.
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10. The method of claim 9 , wherein the spatial layout of the displayed graph is updated in response to inputs from the operator. 12. The method of claim 10 further comprising, by the computing system: in response to receiving an input from the operator indicating selection of an animation option associated with a particular selected node, successively adding edges and nodes to the graph in an animated fashion, wherein each successively added node represents a most common user destination from a previously added node.
| 0.5 |
9,275,139 | 18 | 26 |
18. A method to search audio data, comprising: receiving audio data representing speech; receiving a search query related to the audio data; compiling, by use of a processor, the search query into a hierarchy of scored speech recognition sub-searches; searching, by use of an audio search engine operating in an audio domain, the audio data for speech identified by one or more of the sub-searches to produce hits; and combining, by use of a processor, the hits by use of at least one combination function to provide a composite search score of the audio data, wherein at least one of the combination functions comprises an at-least-M-of-N function, wherein the at-least-M-of-N function produces a high score when at least M members found within a set having membership size of N exceed a predetermined threshold value, wherein N is greater than or equal to M, wherein the composite search score may be determined in accordance with the following relationship: L ab ( x ) = 1 1 + ⅇ a ( x - b ) , wherein: x comprises a vector of scores associated with the hits; a and b comprise sensitivity vectors; and L ab (x) comprises the composite search score.
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18. A method to search audio data, comprising: receiving audio data representing speech; receiving a search query related to the audio data; compiling, by use of a processor, the search query into a hierarchy of scored speech recognition sub-searches; searching, by use of an audio search engine operating in an audio domain, the audio data for speech identified by one or more of the sub-searches to produce hits; and combining, by use of a processor, the hits by use of at least one combination function to provide a composite search score of the audio data, wherein at least one of the combination functions comprises an at-least-M-of-N function, wherein the at-least-M-of-N function produces a high score when at least M members found within a set having membership size of N exceed a predetermined threshold value, wherein N is greater than or equal to M, wherein the composite search score may be determined in accordance with the following relationship: L ab ( x ) = 1 1 + ⅇ a ( x - b ) , wherein: x comprises a vector of scores associated with the hits; a and b comprise sensitivity vectors; and L ab (x) comprises the composite search score. 26. The method of claim 18 , wherein the sensitivity vectors are obtained from user feedback that indicates a correctness of the composite search score.
| 0.586957 |
8,645,300 | 5 | 6 |
5. A method for predicting a navigation destination for a visitor of a webpage belonging to a defined namespace comprising a plurality of webpages, the method comprising: prompting the visitor to indicate an intent on a webpage displayed at a browser of the visitor; receiving the indicated intent from the browser into an intent engine; processing the indicated intent in the intent engine to determine one or more recommended webpages of the plurality of webpages; and causing one or more links to the one or more recommended webpages to be displayed in the webpage at the browser; wherein processing the indicated intent comprises using the indicated intent as a reference to intent ranking data that ranks the plurality of webpages for the indicated intent, the intent ranking data comprising intent data provided by previous visitors to one or more webpages of the namespace.
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5. A method for predicting a navigation destination for a visitor of a webpage belonging to a defined namespace comprising a plurality of webpages, the method comprising: prompting the visitor to indicate an intent on a webpage displayed at a browser of the visitor; receiving the indicated intent from the browser into an intent engine; processing the indicated intent in the intent engine to determine one or more recommended webpages of the plurality of webpages; and causing one or more links to the one or more recommended webpages to be displayed in the webpage at the browser; wherein processing the indicated intent comprises using the indicated intent as a reference to intent ranking data that ranks the plurality of webpages for the indicated intent, the intent ranking data comprising intent data provided by previous visitors to one or more webpages of the namespace. 6. The method according to claim 5 wherein processing the intent comprises determining a ranked list of webpages of the namespace for the indicated intent.
| 0.755521 |
7,855,972 | 20 | 23 |
20. A system for controlling usage of network resources on a communications network based on the identity of an authenticated user, the system comprising: a rule editing module to create one or more packet rules for use on one or more devices of the communications network, each rule including a condition and action to be taken if a packet received at a device satisfies the condition, wherein the one or more packet rules are defined to examine any portion of a packet; a service editing module to create one or more service abstractions, each service abstraction representing a communications network service to be provided to users of the communications network, each service abstraction including a named set of one or more of the packet rules that, in combination, provide the represented communications network service; a role editing module to create, in response to a user, one or more role abstractions associated with an authenticated user, each role abstraction representing a role of an authenticated user with respect to the communications network for controlling usage of network resources on the communications network by the authenticated user, and each role abstraction capable of being assigned a set of one or more of the service abstractions; a user management module to associate the one or more role abstractions with the identity of the authenticated user of the communications network; and storage means comprising memory for storing the one or more created role abstractions, the one or more created service abstractions, or the one or more created packet rules.
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20. A system for controlling usage of network resources on a communications network based on the identity of an authenticated user, the system comprising: a rule editing module to create one or more packet rules for use on one or more devices of the communications network, each rule including a condition and action to be taken if a packet received at a device satisfies the condition, wherein the one or more packet rules are defined to examine any portion of a packet; a service editing module to create one or more service abstractions, each service abstraction representing a communications network service to be provided to users of the communications network, each service abstraction including a named set of one or more of the packet rules that, in combination, provide the represented communications network service; a role editing module to create, in response to a user, one or more role abstractions associated with an authenticated user, each role abstraction representing a role of an authenticated user with respect to the communications network for controlling usage of network resources on the communications network by the authenticated user, and each role abstraction capable of being assigned a set of one or more of the service abstractions; a user management module to associate the one or more role abstractions with the identity of the authenticated user of the communications network; and storage means comprising memory for storing the one or more created role abstractions, the one or more created service abstractions, or the one or more created packet rules. 23. The system of claim 20 , further comprising: a distribution module to distribute the one or more role abstractions to one or more network devices residing on the communications network.
| 0.5 |
8,291,374 | 1 | 4 |
1. A method of automatically generating source code for a programming application, said method comprising the steps of: providing existing source code to be used in part for said programming application; testing said existing source code for functionality to create tested source code; creating abstracted change model representations of a possible set of changes for said tested source code, wherein each of said abstracted change model representations is a change-model and said change model representations collectively are change-models; creating application templates by applying mark-up language to said tested source code; producing generalized implementations of source code changes utilizing said application templates; mapping said generalized implementations of source code changes to at least one selection of a grouping containing said change-models and said tested source code to produce mapped sections of code; accepting inputs in to arrange, configure and assign specific values for said change-model representations; and selectively transforming, in any combination, said tested source code, said change-model representations, said specific values, said generalized implementations and said mapped sections of code in order to produce new source code.
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1. A method of automatically generating source code for a programming application, said method comprising the steps of: providing existing source code to be used in part for said programming application; testing said existing source code for functionality to create tested source code; creating abstracted change model representations of a possible set of changes for said tested source code, wherein each of said abstracted change model representations is a change-model and said change model representations collectively are change-models; creating application templates by applying mark-up language to said tested source code; producing generalized implementations of source code changes utilizing said application templates; mapping said generalized implementations of source code changes to at least one selection of a grouping containing said change-models and said tested source code to produce mapped sections of code; accepting inputs in to arrange, configure and assign specific values for said change-model representations; and selectively transforming, in any combination, said tested source code, said change-model representations, said specific values, said generalized implementations and said mapped sections of code in order to produce new source code. 4. The method according to claim 1 , further including the step of providing at least one user input interface for accepting inputs.
| 0.769231 |
8,775,365 | 28 | 29 |
28. A method of social and interactive knowledge discovery service comprising: receiving one or more inputs from a user through one or more data communication devices; providing an interactive knowledge discovery session interface for the user to interact with a program module comprising instructions configured, when executed using one or more data processing or computing devices, to perform: accessing or building a first one or more data structures corresponding to at least one participation matrix representing participation of ontological subjects of a first predefined order into partitions or ontological subjects of a second predefined order of a body of knowledge; accessing, or building in real time, a second one or more data structures corresponding to association strengths between a plurality of ontological subjects of a predefined order; wherein said association strength is a function of: i. probability of occurrences of some of the ontological subjects of the first order in partitions or ontological subjects of a predefined order of the body of knowledge, and ii. co-occurrences of some ontological subjects of the first order in some of partitions or ontological subjects of a predefined order; accessing evaluated, or evaluating in real time, value significances for one or more partitions or one or more ontological subjects of the body of knowledge, based on data of one or more of said first and second one or more data structures and in respect to at least one significance aspect of the one or more partitions or one or more ontological subjects of the body of knowledge; providing, using one or more data processing or computing devices, at least one output using one or more partitions of the body of knowledge and/or one or more sets of ontological subjects in response to said one or more inputs from the user, based on the evaluated value significances of the one or more partitions and/or one or more ontological subjects of the body of knowledge and the form of response, and providing an environment for interaction between said program module and/or one or more other users respective of the user's one or more inputs so as to have an interactive and/or social session.
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28. A method of social and interactive knowledge discovery service comprising: receiving one or more inputs from a user through one or more data communication devices; providing an interactive knowledge discovery session interface for the user to interact with a program module comprising instructions configured, when executed using one or more data processing or computing devices, to perform: accessing or building a first one or more data structures corresponding to at least one participation matrix representing participation of ontological subjects of a first predefined order into partitions or ontological subjects of a second predefined order of a body of knowledge; accessing, or building in real time, a second one or more data structures corresponding to association strengths between a plurality of ontological subjects of a predefined order; wherein said association strength is a function of: i. probability of occurrences of some of the ontological subjects of the first order in partitions or ontological subjects of a predefined order of the body of knowledge, and ii. co-occurrences of some ontological subjects of the first order in some of partitions or ontological subjects of a predefined order; accessing evaluated, or evaluating in real time, value significances for one or more partitions or one or more ontological subjects of the body of knowledge, based on data of one or more of said first and second one or more data structures and in respect to at least one significance aspect of the one or more partitions or one or more ontological subjects of the body of knowledge; providing, using one or more data processing or computing devices, at least one output using one or more partitions of the body of knowledge and/or one or more sets of ontological subjects in response to said one or more inputs from the user, based on the evaluated value significances of the one or more partitions and/or one or more ontological subjects of the body of knowledge and the form of response, and providing an environment for interaction between said program module and/or one or more other users respective of the user's one or more inputs so as to have an interactive and/or social session. 29. The method of claim 28 , wherein the interactive environment is further configured to represent a user in the interactive environment by a visual object visible on the display device of at least one of the user.
| 0.666149 |
7,761,448 | 1 | 8 |
1. A system for ranking search results, comprising a search engine on a computing device, the search engine configured to execute computer-executable instructions, which when executed by the computing system cause the computing system to perform a method comprising: discovering a plurality of documents on a network; recording document and link information for each of the plurality of documents on the network; generating a representation of the network from the document and link information, wherein the representation of the network includes a plurality of nodes, each document being represented by one of the plurality of nodes; receiving manually input click distances designating a subset of the plurality of nodes as highest authority nodes, the subset of the plurality of nodes including at least a first highest authority node and a second highest authority node, wherein the manually input click distances indicate a relative importance of each highest authority node with respect to other highest authority nodes; initializing click distances for a second subset of the plurality of nodes to a maximum value, the second subset of the plurality of nodes not including highest authority nodes and comprising at least a first non-highest authority node and a second non-highest authority node; computing click distances for the first and second non-highest authority nodes by: determining a first click distance for the first non-highest authority node, the first click distance being a first number of branches traversed on a first shortest path between the first non-highest authority node and the first highest authority node; determining a second click distance for the first non-highest authority node, the second click distance being a second number of branches traversed on a second shortest path between the first non-highest authority node and the second highest authority node; determining a third click distance for the second non-highest authority node, the third click distance being a third number of branches traversed on a third shortest path between the second non-highest authority node and the first highest authority node; and determining a fourth click distance for the second non-highest authority node, the fourth click distance being a fourth number of branches traversed on a fourth shortest path between the second non-highest authority node and the second highest authority node; storing the first, second, third, and fourth click distances in memory, such that the first and second click distances are associated with a first document, and the third and fourth click distances are associated with a second document; calculating search rank results using at least one of the first, second, third, and fourth click distances associated with each of the first and second documents as a query-independent relevance measure in ranking the plurality of documents; and storing search rank results in memory, wherein the search rank results comprise a list of documents arranged in a descending order of relevance.
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1. A system for ranking search results, comprising a search engine on a computing device, the search engine configured to execute computer-executable instructions, which when executed by the computing system cause the computing system to perform a method comprising: discovering a plurality of documents on a network; recording document and link information for each of the plurality of documents on the network; generating a representation of the network from the document and link information, wherein the representation of the network includes a plurality of nodes, each document being represented by one of the plurality of nodes; receiving manually input click distances designating a subset of the plurality of nodes as highest authority nodes, the subset of the plurality of nodes including at least a first highest authority node and a second highest authority node, wherein the manually input click distances indicate a relative importance of each highest authority node with respect to other highest authority nodes; initializing click distances for a second subset of the plurality of nodes to a maximum value, the second subset of the plurality of nodes not including highest authority nodes and comprising at least a first non-highest authority node and a second non-highest authority node; computing click distances for the first and second non-highest authority nodes by: determining a first click distance for the first non-highest authority node, the first click distance being a first number of branches traversed on a first shortest path between the first non-highest authority node and the first highest authority node; determining a second click distance for the first non-highest authority node, the second click distance being a second number of branches traversed on a second shortest path between the first non-highest authority node and the second highest authority node; determining a third click distance for the second non-highest authority node, the third click distance being a third number of branches traversed on a third shortest path between the second non-highest authority node and the first highest authority node; and determining a fourth click distance for the second non-highest authority node, the fourth click distance being a fourth number of branches traversed on a fourth shortest path between the second non-highest authority node and the second highest authority node; storing the first, second, third, and fourth click distances in memory, such that the first and second click distances are associated with a first document, and the third and fourth click distances are associated with a second document; calculating search rank results using at least one of the first, second, third, and fourth click distances associated with each of the first and second documents as a query-independent relevance measure in ranking the plurality of documents; and storing search rank results in memory, wherein the search rank results comprise a list of documents arranged in a descending order of relevance. 8. The system of claim 1 wherein calculating the search rank results further comprises ranking the first and second documents according to a scoring function (score) that is determined according to at least: the at least one of the click distances associated with each of the first and second documents (CD), a weighted term frequency (wtf), a weighted document length (wdl), an average weighted document length (avwdl), a number of documents on the network (N); a number of documents containing a query term (n), a weight of a query-independent component (W cd ), a weight of the click distance (b cd ), a weight of a URL depth (b ud ), the URL depth (UD), a click distance saturation constant (K cd ) and other constant (k 1 ,b).
| 0.5 |
10,025,564 | 8 | 13 |
8. A computer program product for generating and implementing intuitively comfortable frames of task appropriate frames of reference for multiple dimensions of context constraints for related sets of objects within an integrated development environment (IDE), the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising: identifying a first hierarchical set of context constraints for a first object, wherein the first hierarchical set of context constraints for the first object includes multiple facets of context, and wherein the multiple facets of context comprise an operational environment context describing an operating system and hardware platform that must be used by the first object; depicting the first hierarchical set of context constraints for the first object on the IDE, wherein the first hierarchical set of context constraints is depicted by utilizing a visual metaphor selected by a user, wherein the visual metaphor selected by the user is a hierarchical stack of planes and pillars, wherein a top plane represents a top context for the first object, wherein a pillar connects the top plane to a lower plane that represents a lower context for the first object, and wherein the lower context supports the top context just as the lower plane supports the top plane via the pillar; receiving a first zoom-in input from the user, wherein the first zoom-in input is for a first context constraint in the first hierarchical set of context constraints; in response to receiving the first zoom-in input, placing the IDE in mention mode, wherein use of the first hierarchical set of context constraints against the first object is disabled while the IDE is in mention mode; in response to the IDE being placed in mention mode, displaying detail of the first context constraint on the IDE; and receiving changes to the first context constraint that are input by the user from the IDE to create a modified first context constraint on the first object.
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8. A computer program product for generating and implementing intuitively comfortable frames of task appropriate frames of reference for multiple dimensions of context constraints for related sets of objects within an integrated development environment (IDE), the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code readable and executable by a processor to perform a method comprising: identifying a first hierarchical set of context constraints for a first object, wherein the first hierarchical set of context constraints for the first object includes multiple facets of context, and wherein the multiple facets of context comprise an operational environment context describing an operating system and hardware platform that must be used by the first object; depicting the first hierarchical set of context constraints for the first object on the IDE, wherein the first hierarchical set of context constraints is depicted by utilizing a visual metaphor selected by a user, wherein the visual metaphor selected by the user is a hierarchical stack of planes and pillars, wherein a top plane represents a top context for the first object, wherein a pillar connects the top plane to a lower plane that represents a lower context for the first object, and wherein the lower context supports the top context just as the lower plane supports the top plane via the pillar; receiving a first zoom-in input from the user, wherein the first zoom-in input is for a first context constraint in the first hierarchical set of context constraints; in response to receiving the first zoom-in input, placing the IDE in mention mode, wherein use of the first hierarchical set of context constraints against the first object is disabled while the IDE is in mention mode; in response to the IDE being placed in mention mode, displaying detail of the first context constraint on the IDE; and receiving changes to the first context constraint that are input by the user from the IDE to create a modified first context constraint on the first object. 13. The computer program product of claim 8 , wherein the method further comprises: depicting on the IDE only a context constraint that is at a top of the first hierarchical set of context constraints while the first hierarchical set of context constraints are being currently enforced against the first object that is presently executing.
| 0.81019 |
9,070,435 | 1 | 8 |
1. A pre-computation based ternary content addressable memory (TCAM), comprising: a counter configured to generate a count of a number of ones or zeros in a search word; a primary TCAM configured to store a data word; and a secondary TCAM configured to store a pre-computation word representing a range inclusive of a lower and upper bound of a number of ones or zeros possible in the data word, wherein the secondary TCAM is configured to disable pre-charging of a match line associated with the data word if the count of the number of ones or zeroes in the search word does not fall within the range represented by the pre-computation word.
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1. A pre-computation based ternary content addressable memory (TCAM), comprising: a counter configured to generate a count of a number of ones or zeros in a search word; a primary TCAM configured to store a data word; and a secondary TCAM configured to store a pre-computation word representing a range inclusive of a lower and upper bound of a number of ones or zeros possible in the data word, wherein the secondary TCAM is configured to disable pre-charging of a match line associated with the data word if the count of the number of ones or zeroes in the search word does not fall within the range represented by the pre-computation word. 8. The pre-computation based TCAM of claim 1 , wherein the secondary TCAM is configured to disable pre-charging of match lines associated with a plurality of data words stored in the primary TCAM if the count does not fall within the range represented by the pre-computation word.
| 0.5 |
9,201,936 | 2 | 3 |
2. The information handling system of claim 1 wherein the processors perform additional actions comprising: storing the one or more schema terms in a schema terms dictionary; providing the one or more schema terms stored in the schema terms dictionary to a user; receiving one or more schema term selections from the user that selects one or more of the schema terms; and including the selected schema terms in the query during the creation of the query.
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2. The information handling system of claim 1 wherein the processors perform additional actions comprising: storing the one or more schema terms in a schema terms dictionary; providing the one or more schema terms stored in the schema terms dictionary to a user; receiving one or more schema term selections from the user that selects one or more of the schema terms; and including the selected schema terms in the query during the creation of the query. 3. The information handling system of claim 2 wherein the one or more storage areas are accessible to the user for analytical processing.
| 0.5 |
9,020,866 | 17 | 19 |
17. A non-transitory computer readable storage medium storing one or more sequences of instructions executable by one or more processors to perform a set of operations comprising: training a first ranking function that uses online data computed at a time of receiving a search request and stored in an index to produce a first ranking score for an item among a plurality of items, the online data includes a set of search results including at least information about a product; training a second ranking function to produce a second ranking score for the item, the second ranking function trained using a boost method, the second ranking function using offline data unavailable in the index in combination with the first ranking score produced by the first ranking function; and ranking the item among a plurality of items based at least in part on both the first ranking score and the second ranking score, the item is the product in a database of products accessible on a network, wherein ranking the item is performed to determine a relevance of the item among the search results in a context of the search request.
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17. A non-transitory computer readable storage medium storing one or more sequences of instructions executable by one or more processors to perform a set of operations comprising: training a first ranking function that uses online data computed at a time of receiving a search request and stored in an index to produce a first ranking score for an item among a plurality of items, the online data includes a set of search results including at least information about a product; training a second ranking function to produce a second ranking score for the item, the second ranking function trained using a boost method, the second ranking function using offline data unavailable in the index in combination with the first ranking score produced by the first ranking function; and ranking the item among a plurality of items based at least in part on both the first ranking score and the second ranking score, the item is the product in a database of products accessible on a network, wherein ranking the item is performed to determine a relevance of the item among the search results in a context of the search request. 19. The non-transitory computer readable storage medium of claim 17 , wherein the boosting method is a gradient boosting method.
| 0.807808 |
8,800,029 | 5 | 6 |
5. A computer-readable storage device storing computer instructions, which, when executed, enables a computer system operating with a reputation provider for collecting and maintaining historical party reputation data and for using the historical party reputation data to calculate an access decision rating, the computer-readable storage medium storing computer instructions comprising: collecting reputation information of a requester, the requester comprising a first user that is requesting access to one or more assets, and the reputation information is based on at least an association of the first user with an organization and an association of the first user with one or more other users associated with one or more other organizations; storing the requester's reputation information; calculating the access decision rating based upon the requester's reputation information; storing the access decision rating; determining a change in the requester's reputation information, wherein the change comprises at least one of: a) the first user forming a new association with another organization or b) the first user forming a new association with a second user, wherein the second user is affiliated with another organization; and causing a new access decision rating to be calculated based upon the determined change in the requester's reputation information.
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5. A computer-readable storage device storing computer instructions, which, when executed, enables a computer system operating with a reputation provider for collecting and maintaining historical party reputation data and for using the historical party reputation data to calculate an access decision rating, the computer-readable storage medium storing computer instructions comprising: collecting reputation information of a requester, the requester comprising a first user that is requesting access to one or more assets, and the reputation information is based on at least an association of the first user with an organization and an association of the first user with one or more other users associated with one or more other organizations; storing the requester's reputation information; calculating the access decision rating based upon the requester's reputation information; storing the access decision rating; determining a change in the requester's reputation information, wherein the change comprises at least one of: a) the first user forming a new association with another organization or b) the first user forming a new association with a second user, wherein the second user is affiliated with another organization; and causing a new access decision rating to be calculated based upon the determined change in the requester's reputation information. 6. The computer-readable storage device of claim 5 further comprising computer instructions comprising using the access decision rating when an access decision is necessary.
| 0.511299 |
8,289,134 | 11 | 13 |
11. A security system comprising: a plurality of sensors configured to sense security breaches and generate detection signals based thereon; a controller configured to receive the detection signals from the plurality of sensors and selectively generate an alarm signal in response to the detection signals; a database accessible by the controller, the database storing a user identification for each of a plurality of users of the security system and a preferred language for communicating with each of the plurality of users of the security system, the preferred language being selected from a plurality of different available languages; and a user interface in communication with the controller, the user interface comprising an input device configured to receive a user identification to identify a particular user and a communication device configured to communicate with the particular user in the user's preferred language, and wherein in response to at least one of the sensors sensing a security breach, the communication device provides an indication to the particular user that an alarm signal will be issued, the indication being provided in the particular user's preferred language and including instructions given in the particular user's preferred language regarding how to abort the alarm signal.
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11. A security system comprising: a plurality of sensors configured to sense security breaches and generate detection signals based thereon; a controller configured to receive the detection signals from the plurality of sensors and selectively generate an alarm signal in response to the detection signals; a database accessible by the controller, the database storing a user identification for each of a plurality of users of the security system and a preferred language for communicating with each of the plurality of users of the security system, the preferred language being selected from a plurality of different available languages; and a user interface in communication with the controller, the user interface comprising an input device configured to receive a user identification to identify a particular user and a communication device configured to communicate with the particular user in the user's preferred language, and wherein in response to at least one of the sensors sensing a security breach, the communication device provides an indication to the particular user that an alarm signal will be issued, the indication being provided in the particular user's preferred language and including instructions given in the particular user's preferred language regarding how to abort the alarm signal. 13. The system of claim 11 , wherein the input device includes at least one of a keypad, a microphone, a wireless receiver, a data reader, and a biometric sensor.
| 0.725424 |
8,593,404 | 16 | 17 |
16. The keyboard of claim 15 , wherein the at least one vowel key is a single key having all the vowels associated therewith, with the vowel key being positioned in a row below the first set of keys.
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16. The keyboard of claim 15 , wherein the at least one vowel key is a single key having all the vowels associated therewith, with the vowel key being positioned in a row below the first set of keys. 17. The keyboard of claim 16 , wherein the at least one vowel key is positioned in a row with at least some of the additional set of keys.
| 0.5 |
8,947,322 | 1 | 11 |
1. A method implemented by a head-mountable device comprising: receiving, by the head-mountable computing device, input data that is indicative of head position; providing, by the head-mountable computing device, a user-interface that comprises a content region containing a set of selectable content objects that are horizontally arranged, wherein the content region is located at a fixed height within the user-interface; defining, by the head-mountable computing device, a view region that is movable within the user-interface, wherein the view region is smaller than the user-interface; associating, by the head-mountable computing device, a forward-looking head position with a first location of the view region within the user-interface, wherein the fixed height of the content region is such that at least a portion of the content region is located above the view region, when the view region is at the first location associated with forward-looking head position; based on head movement data, moving the view region within the user-interface, wherein the head movement data is determined based on the input data that is indicative of head position; as the view region moves within the user-interface, displaying a portion of the user-interface corresponding to the view region in the see-through display; determining a first user-context associated with the head-mountable device; and dynamically changing the set of selectable content objects contained in the content region based on the determined first user-context.
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1. A method implemented by a head-mountable device comprising: receiving, by the head-mountable computing device, input data that is indicative of head position; providing, by the head-mountable computing device, a user-interface that comprises a content region containing a set of selectable content objects that are horizontally arranged, wherein the content region is located at a fixed height within the user-interface; defining, by the head-mountable computing device, a view region that is movable within the user-interface, wherein the view region is smaller than the user-interface; associating, by the head-mountable computing device, a forward-looking head position with a first location of the view region within the user-interface, wherein the fixed height of the content region is such that at least a portion of the content region is located above the view region, when the view region is at the first location associated with forward-looking head position; based on head movement data, moving the view region within the user-interface, wherein the head movement data is determined based on the input data that is indicative of head position; as the view region moves within the user-interface, displaying a portion of the user-interface corresponding to the view region in the see-through display; determining a first user-context associated with the head-mountable device; and dynamically changing the set of selectable content objects contained in the content region based on the determined first user-context. 11. The method of claim 1 , further comprising: receiving input selecting one or more content objects from the set of selectable content objects contained in the content region; and displaying in the view region content associated with the selected one or more content objects.
| 0.950589 |
9,524,307 | 1 | 2 |
1. A method for performing error checking on a structured document, comprising: performing by a first thread executing on at least one of one or more processors that are capable of performing multi-threaded executions: identifying one or more new elements in the document; assigning an identifier (ID) to each new element; and storing a copy of each new element in a first queue, the copy of each new element including the ID associated with the new element and at least one of text and structural information associated with the new element; and performing by a second thread executing on the at least one of the one or more processors: retrieving each copy of each new element from the first queue; applying error checking to each retrieved copy of each new element to detect errors associated therewith; and in response to detecting an error associated with a retrieved copy of a respective new element, generating an error checking result comprising at least the ID associated with the retrieved copy of the respective new element.
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1. A method for performing error checking on a structured document, comprising: performing by a first thread executing on at least one of one or more processors that are capable of performing multi-threaded executions: identifying one or more new elements in the document; assigning an identifier (ID) to each new element; and storing a copy of each new element in a first queue, the copy of each new element including the ID associated with the new element and at least one of text and structural information associated with the new element; and performing by a second thread executing on the at least one of the one or more processors: retrieving each copy of each new element from the first queue; applying error checking to each retrieved copy of each new element to detect errors associated therewith; and in response to detecting an error associated with a retrieved copy of a respective new element, generating an error checking result comprising at least the ID associated with the retrieved copy of the respective new element. 2. The method of claim 1 , wherein the generating the error checking result comprises: generating the error checking result comprising at least the ID associated with the retrieved copy of the respective new element and an error type.
| 0.672269 |
7,523,079 | 1 | 2 |
1. A computer-implemented network structure, comprising: a memory that stores instructions to create: a first node that is a semantic Janus unit, wherein the first node possesses an existing time-variable state; a second node containing informational contents; and a link between the first node and the second node, wherein the link contains relational contents that describes the relationship between the first node and the second node, wherein the first node carries out operations on the second node and on the link, wherein the existing time-variable state determines which operations are carried out, and wherein a pattern in an image is recognized by carrying out the operations.
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1. A computer-implemented network structure, comprising: a memory that stores instructions to create: a first node that is a semantic Janus unit, wherein the first node possesses an existing time-variable state; a second node containing informational contents; and a link between the first node and the second node, wherein the link contains relational contents that describes the relationship between the first node and the second node, wherein the first node carries out operations on the second node and on the link, wherein the existing time-variable state determines which operations are carried out, and wherein a pattern in an image is recognized by carrying out the operations. 2. The computer-implemented network structure of claim 1 , further comprising: a library of elementary links, wherein the first node, the second node and the link are part of a semantic network machine within the computer-implemented network structure, wherein the computer-implemented network structure has a user, and wherein the user selects the link from the library of elementary links and adds the link to the semantic network machine.
| 0.502257 |
8,886,579 | 1 | 9 |
1. A computer-implemented method of training a neural network, comprising: training a first neural network of a self organizing map type with a first set of first text documents each containing one or more keywords in a semantic context to map each document to a point in the self organizing map by semantic clustering; performing a reverse indexing by determining, for each keyword occurring in the first set, all points in the self organizing map to which first documents containing said keyword are mapped, and storing said mapped points as a pattern for said keyword in a pattern dictionary; forming at least one sequence of keywords from a second set of second text documents each containing one or more keywords in a semantic context; translating said at least one sequence of keywords into at least one sequence of patterns by using said pattern dictionary; and training a second target neural network with said at least one sequence of patterns.
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1. A computer-implemented method of training a neural network, comprising: training a first neural network of a self organizing map type with a first set of first text documents each containing one or more keywords in a semantic context to map each document to a point in the self organizing map by semantic clustering; performing a reverse indexing by determining, for each keyword occurring in the first set, all points in the self organizing map to which first documents containing said keyword are mapped, and storing said mapped points as a pattern for said keyword in a pattern dictionary; forming at least one sequence of keywords from a second set of second text documents each containing one or more keywords in a semantic context; translating said at least one sequence of keywords into at least one sequence of patterns by using said pattern dictionary; and training a second target neural network with said at least one sequence of patterns. 9. The method of claim 1 , comprising: translating said at least one keyword into at least one pattern by means of the pattern dictionary; feeding said at least one pattern as an input pattern into said trained second neural network; obtaining at least one output pattern from said trained second neural network; and translating said at least output pattern into at least one keyword by means of the pattern dictionary.
| 0.5 |
8,793,265 | 48 | 51 |
48. The client module of claim 46 , wherein the selector further includes an updating module configured for accumulating scores over multiple searches for each selected personalized search engine as a function of the quality of the search results for subsequent queries based on the characteristic information.
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48. The client module of claim 46 , wherein the selector further includes an updating module configured for accumulating scores over multiple searches for each selected personalized search engine as a function of the quality of the search results for subsequent queries based on the characteristic information. 51. The client module of claim 48 , wherein the updating module is further configured for obtaining an intermediate score based on the weighted sum of frequencies of occurrences.
| 0.555 |
9,760,343 | 10 | 11 |
10. The integrated development environment of claim 8 wherein the build script engine comprises: a rules configuration block; a task scheduler; and wherein the rules configuration block and task scheduler determine scheduling of build actions of the processed build rules from the build rules parser, the scheduling of build actions are provided to the build script generator for generating the build scripts.
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10. The integrated development environment of claim 8 wherein the build script engine comprises: a rules configuration block; a task scheduler; and wherein the rules configuration block and task scheduler determine scheduling of build actions of the processed build rules from the build rules parser, the scheduling of build actions are provided to the build script generator for generating the build scripts. 11. The integrated development environment of claim 10 wherein: the build script engine comprises a delta detection block, the delta detection block compares the processed App metadata, processed build rules and source code of the hybrid App with App metadata, build rules and source code of a previous version of the hybrid App, and generates a delta list comprising build steps based on the differences; and the build script generator generates the build scripts based on the build rules, App metadata, delta list and scheduling of build actions.
| 0.5 |
8,645,141 | 1 | 3 |
1. A method of performing text to speech conversion on a portable device, said method comprising: predicting, based at least in part on prior user selection of at least one second book and on a first book being newly released and prior to user selection of listening to an audio version of the first book, the first book being different from the second book, the first book for conversion to speech format, by anticipating the first book based on at least one feature of the first book, the at least one feature being new release of the first book; responsive to the predicting and prior to user selection to listen to the audio version of the first book, performing a text to speech conversion on said book to produce converted speech; storing said converted speech into a memory device of said portable device; executing a reader application wherein a user request is received for narration of said book; and during said executing, accessing said converted speech from said memory device and rendering said converted speech on said portable device responsive to said user request.
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1. A method of performing text to speech conversion on a portable device, said method comprising: predicting, based at least in part on prior user selection of at least one second book and on a first book being newly released and prior to user selection of listening to an audio version of the first book, the first book being different from the second book, the first book for conversion to speech format, by anticipating the first book based on at least one feature of the first book, the at least one feature being new release of the first book; responsive to the predicting and prior to user selection to listen to the audio version of the first book, performing a text to speech conversion on said book to produce converted speech; storing said converted speech into a memory device of said portable device; executing a reader application wherein a user request is received for narration of said book; and during said executing, accessing said converted speech from said memory device and rendering said converted speech on said portable device responsive to said user request. 3. The method of claim 1 wherein said at least one feature further comprises a playlist of books.
| 0.72905 |
7,774,348 | 12 | 13 |
12. The storage medium of claim 1 wherein the location is identified based on at least one of an explicit location in the query, an IP address, user information, a root term analysis, or combinations thereof.
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12. The storage medium of claim 1 wherein the location is identified based on at least one of an explicit location in the query, an IP address, user information, a root term analysis, or combinations thereof. 13. The storage medium of claim 12 wherein the explicit location in the query is a location term that is combined with the root term of the query.
| 0.5 |
5,526,475 | 1 | 7 |
1. A computer-based method for performing live symbolic mathematical operations in a mathematical document editor, said mathematical document editor capable of editing and processing a mathematical document and controlled by a computer having a screen capable of displaying the mathematical document, the method comprising the steps of: placing mathematical expressions in standard mathematical form at any position on the mathematical document, a subset of the mathematical expressions comprising a symbolic evaluation operator; maintaining a dependency graph so that the dependency graph continuously represents mathematical dependencies between the mathematical expressions in the mathematical document; symbolically evaluating each mathematical expression in the mathematical document that includes the symbolic evaluation operator, said step of symbolically evaluating including performing, for each mathematical expression that includes the symbolic evaluation operator, the substeps of (i) utilizing the dependency graph to ascertain all mathematical expressions on which the mathematical expression that includes the symbolic evaluation operator directly and indirectly depend, and (ii) passing the mathematical expression that includes the symbolic evaluation operator and the mathematical expressions ascertained at substep (i) to a symbolic algebra engine for symbolic evaluation; displaying in the mathematical document results of the symbolic evaluation of each mathematical expression evaluated at the previous step; editing a mathematical expression in the mathematical document; and automatically updating the mathematical document whenever a mathematical expression is edited by utilizing the dependency graph to take into account all mathematical dependencies in the mathematical document so that all mathematical expressions comprising the symbolic evaluation operator are consistent with all antecedent mathematical expressions upon which said mathematical expressions comprising the symbolic evaluation operator depend, said step of automatically updating including the substeps of (a) utilizing the dependency graph to ascertain if a mathematical expression that includes the symbolic evaluation operator depends upon the edited mathematical expression, (b) utilizing the dependency graph to determine all mathematical expressions on which the mathematical expression that includes the symbolic evaluation operator ascertained at substep (a) depends, and (c) passing the edited mathematical expression, the mathematical expression that includes the symbolic evaluation operator ascertained at substep (a) and the mathematical expressions determined at substep (b) to the symbolic algebra engine for symbolic evaluation.
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1. A computer-based method for performing live symbolic mathematical operations in a mathematical document editor, said mathematical document editor capable of editing and processing a mathematical document and controlled by a computer having a screen capable of displaying the mathematical document, the method comprising the steps of: placing mathematical expressions in standard mathematical form at any position on the mathematical document, a subset of the mathematical expressions comprising a symbolic evaluation operator; maintaining a dependency graph so that the dependency graph continuously represents mathematical dependencies between the mathematical expressions in the mathematical document; symbolically evaluating each mathematical expression in the mathematical document that includes the symbolic evaluation operator, said step of symbolically evaluating including performing, for each mathematical expression that includes the symbolic evaluation operator, the substeps of (i) utilizing the dependency graph to ascertain all mathematical expressions on which the mathematical expression that includes the symbolic evaluation operator directly and indirectly depend, and (ii) passing the mathematical expression that includes the symbolic evaluation operator and the mathematical expressions ascertained at substep (i) to a symbolic algebra engine for symbolic evaluation; displaying in the mathematical document results of the symbolic evaluation of each mathematical expression evaluated at the previous step; editing a mathematical expression in the mathematical document; and automatically updating the mathematical document whenever a mathematical expression is edited by utilizing the dependency graph to take into account all mathematical dependencies in the mathematical document so that all mathematical expressions comprising the symbolic evaluation operator are consistent with all antecedent mathematical expressions upon which said mathematical expressions comprising the symbolic evaluation operator depend, said step of automatically updating including the substeps of (a) utilizing the dependency graph to ascertain if a mathematical expression that includes the symbolic evaluation operator depends upon the edited mathematical expression, (b) utilizing the dependency graph to determine all mathematical expressions on which the mathematical expression that includes the symbolic evaluation operator ascertained at substep (a) depends, and (c) passing the edited mathematical expression, the mathematical expression that includes the symbolic evaluation operator ascertained at substep (a) and the mathematical expressions determined at substep (b) to the symbolic algebra engine for symbolic evaluation. 7. The method of claim 1 wherein the mathematical expressions include mathematical definitions.
| 0.75641 |
9,015,160 | 8 | 14 |
8. A computer-implemented method, comprising: accessing text by a processing system; identifying, by the processing system, a plurality of terms from the text; determining, by the processing system, a plurality of term vectors associated with the identified terms; calculating a weight of each of the determined term vectors; clustering, by the processing system, the determined term vectors into a plurality of clusters, each of the clusters being related to a distinct concept of the text, each cluster comprising at least one of the determined term vectors, the clustering comprising selecting the at least one of the determined term vectors based on the determined weights of the term vectors and distances between the determined term vectors; creating, by the processing system, a first pseudo-document according to a first cluster of the plurality of clusters and a second pseudo-document according to a second cluster of the plurality of clusters; identifying, by the processing system using latent semantic analysis (LSA), a first set of terms associated with the first cluster and a second set of terms associated with the second cluster; determining a first weight associated with the first cluster and a second weight associated with the second cluster, wherein the first weight is based at least on the determined weights of the term vectors of the first cluster, and wherein the second weight is based at least on the determined weights of the term vectors of the second cluster; determining a first percentage of a list of output terms that should come from the first cluster and a second percentage of the list of output terms that should come from the second cluster, the first percentage based on a ratio of the first weight to a sum of the first and second weights, the second percentage based on a ratio of the second weight to the sum of the first and second weights; selecting one or more terms from the first set of terms according to the determined first percentage; selecting one or more terms from the second set of terms according to the determined second percentage; creating, by the processing system, the list of output terms using at least a portion of the selected terms from the first and second sets of terms, the list of output terms having the distinct concepts of the plurality of clusters; and storing the list of output terms in one or more memory units.
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8. A computer-implemented method, comprising: accessing text by a processing system; identifying, by the processing system, a plurality of terms from the text; determining, by the processing system, a plurality of term vectors associated with the identified terms; calculating a weight of each of the determined term vectors; clustering, by the processing system, the determined term vectors into a plurality of clusters, each of the clusters being related to a distinct concept of the text, each cluster comprising at least one of the determined term vectors, the clustering comprising selecting the at least one of the determined term vectors based on the determined weights of the term vectors and distances between the determined term vectors; creating, by the processing system, a first pseudo-document according to a first cluster of the plurality of clusters and a second pseudo-document according to a second cluster of the plurality of clusters; identifying, by the processing system using latent semantic analysis (LSA), a first set of terms associated with the first cluster and a second set of terms associated with the second cluster; determining a first weight associated with the first cluster and a second weight associated with the second cluster, wherein the first weight is based at least on the determined weights of the term vectors of the first cluster, and wherein the second weight is based at least on the determined weights of the term vectors of the second cluster; determining a first percentage of a list of output terms that should come from the first cluster and a second percentage of the list of output terms that should come from the second cluster, the first percentage based on a ratio of the first weight to a sum of the first and second weights, the second percentage based on a ratio of the second weight to the sum of the first and second weights; selecting one or more terms from the first set of terms according to the determined first percentage; selecting one or more terms from the second set of terms according to the determined second percentage; creating, by the processing system, the list of output terms using at least a portion of the selected terms from the first and second sets of terms, the list of output terms having the distinct concepts of the plurality of clusters; and storing the list of output terms in one or more memory units. 14. The computer-implemented method of claim 8 , wherein: the weights of each of the determined term vectors comprise log-entropy weights; the first weight associated with the first cluster comprises a sum of the determined log-entropy weights of the term vectors of the first cluster; and the second weight associated with the second cluster comprises a sum of the determined log-entropy weights of the term vectors of the second cluster.
| 0.5 |
7,954,115 | 4 | 5 |
4. The computer-implementable method of claim 1 further comprising providing a server accessible by said management module for the management of said network-based community portal and said mashup platform.
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4. The computer-implementable method of claim 1 further comprising providing a server accessible by said management module for the management of said network-based community portal and said mashup platform. 5. The computer-implementable method of claim 4 wherein said server comprises a widget server.
| 0.5 |
8,706,713 | 1 | 10 |
1. A method of searching for desired information, the method comprising: receiving, from a user having user profile data associated therewith, a search request comprising a search argument; providing, to a first search engine, the received search argument for correlation with first contextual information in a database of network related information; providing, to a second search engine, the received search argument and the user profile data for correlation with a first advertisement in an advertisement database; providing the first contextual information and the first advertisement to the user as a first search result; updating the user profile data based on at least one of the first contextual information, the first advertisement, selection of the first advertisement by the user, and non-selection of the first advertisement by the user; receiving refinement information comprising a refined search argument from the user; providing, to the first search engine, the refined search argument for correlation with second contextual information in the database of network related information; providing, to the second search engine, the refined search argument and the updated user profile data for correlation with a second advertisement in the advertisement database; and providing the second contextual information and the second advertisement to the user.
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1. A method of searching for desired information, the method comprising: receiving, from a user having user profile data associated therewith, a search request comprising a search argument; providing, to a first search engine, the received search argument for correlation with first contextual information in a database of network related information; providing, to a second search engine, the received search argument and the user profile data for correlation with a first advertisement in an advertisement database; providing the first contextual information and the first advertisement to the user as a first search result; updating the user profile data based on at least one of the first contextual information, the first advertisement, selection of the first advertisement by the user, and non-selection of the first advertisement by the user; receiving refinement information comprising a refined search argument from the user; providing, to the first search engine, the refined search argument for correlation with second contextual information in the database of network related information; providing, to the second search engine, the refined search argument and the updated user profile data for correlation with a second advertisement in the advertisement database; and providing the second contextual information and the second advertisement to the user. 10. The method of claim 1 , further comprising maintaining a user profile associated with the user.
| 0.758537 |
4,005,388 | 22 | 23 |
22. An interactive terminal, for communicating with external data processing means, comprising: A. an alpha-numeric display for visually presenting data received and transmitted; B. a data memory communicating with said display for storage of information received and transmitted; C. an information entry keyboard operable by the user's first hand wherein each of a plurality of said keys represents a transmission of "n" different information levels; "n" being an integer greater than 1; D. shift level control keys operable by the user's second hand for selecting the desired information level for transmission of all "n" levels, wherein the minimum number of shift level control keys is determined by the two following formulae depending upon the value of "n", 1. (log .sub.2 n), for "n" equal to an integral value of 2, and 2. (1 + the truncated value of log .sub.2 n) for "n" not equal to an integral value of 2; E. information transmission means communicating with said keyboard and said shift level control keys for transmitting selected information to at least said external data processing means; F. information receiving means communicating with said external data processing means and said data memory for receipt of information; and G. housing means dimensioned for the palm of the user's second hand, having a front face dimensioned for mounting said keyboard, and at least one side dimensioned for mounting said shift level control keys so as to be operable by the user's second hand when holding said housing means; whereby the fingers of the user's second hand select desired shift level control keys and the other hand selects desired keys of the information entry keyboard.
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22. An interactive terminal, for communicating with external data processing means, comprising: A. an alpha-numeric display for visually presenting data received and transmitted; B. a data memory communicating with said display for storage of information received and transmitted; C. an information entry keyboard operable by the user's first hand wherein each of a plurality of said keys represents a transmission of "n" different information levels; "n" being an integer greater than 1; D. shift level control keys operable by the user's second hand for selecting the desired information level for transmission of all "n" levels, wherein the minimum number of shift level control keys is determined by the two following formulae depending upon the value of "n", 1. (log .sub.2 n), for "n" equal to an integral value of 2, and 2. (1 + the truncated value of log .sub.2 n) for "n" not equal to an integral value of 2; E. information transmission means communicating with said keyboard and said shift level control keys for transmitting selected information to at least said external data processing means; F. information receiving means communicating with said external data processing means and said data memory for receipt of information; and G. housing means dimensioned for the palm of the user's second hand, having a front face dimensioned for mounting said keyboard, and at least one side dimensioned for mounting said shift level control keys so as to be operable by the user's second hand when holding said housing means; whereby the fingers of the user's second hand select desired shift level control keys and the other hand selects desired keys of the information entry keyboard. 23. An interactive terminal as defined in claim 22, further comprising: H. scroll switching means communicating with said memory for presenting on said display any data held in said memory.
| 0.5 |
7,685,141 | 8 | 17 |
8. A method as recited in claim 1 , wherein the score value for the candidate path relationship includes a second measure that indicates how rare the candidate path relationship is in the entity relationship graph.
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8. A method as recited in claim 1 , wherein the score value for the candidate path relationship includes a second measure that indicates how rare the candidate path relationship is in the entity relationship graph. 17. A computer-readable storage medium carrying one or more sequences of instructions which, when executed by one or more processors, causes the one or more processors to perform the method recited in claim 8 .
| 0.5 |
8,428,241 | 13 | 15 |
13. The apparatus of claim 11 , wherein the at least one processor is further programmed to associate the recorded speech that represents the request by the caller for the destination with the recorded destination identifying information, and update a destination map using the recorded speech that is associated with the recorded destination identifying information.
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13. The apparatus of claim 11 , wherein the at least one processor is further programmed to associate the recorded speech that represents the request by the caller for the destination with the recorded destination identifying information, and update a destination map using the recorded speech that is associated with the recorded destination identifying information. 15. The apparatus of claim 13 , wherein the updated destination map is accessible to one or more call handling systems.
| 0.71934 |
9,003,281 | 1 | 10 |
1. An image processing apparatus capable of executing a plurality of processes, the apparatus comprising: a process designation accepting portion to accept designation of at least one of said plurality of processes; a workflow generating portion to generate a workflow defining said one or more processes accepted; a help information storage portion to store help information associating for each of the plurality of processes a process name as identification information for identification of each of the plurality of processes with a process explanation as an explanation of each of the plurality of processes; a help document generating portion to generate a help document corresponding to said generated workflow, wherein said help document generating portion includes a summary page generating portion to generate a summary page having listed thereon identification information for identification of each of said one or more processes defined by said corresponding workflow generated by said workflow generating portion; a display control portion to control display of the help document generated, and a details page generating portion to read one or more help information items corresponding respectively to the one or more processes defined by the generated workflow to generate one or more details pages respectively including the one or more help information items read; and an associating portion to associate identification information items of the one or more processes included in the summary page with the one or more details pages generated, wherein the display control portion, in a case where any one of the identification information items of the one or more processes included in the summary page is designated, displays the details page associated with the identification information items designated.
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1. An image processing apparatus capable of executing a plurality of processes, the apparatus comprising: a process designation accepting portion to accept designation of at least one of said plurality of processes; a workflow generating portion to generate a workflow defining said one or more processes accepted; a help information storage portion to store help information associating for each of the plurality of processes a process name as identification information for identification of each of the plurality of processes with a process explanation as an explanation of each of the plurality of processes; a help document generating portion to generate a help document corresponding to said generated workflow, wherein said help document generating portion includes a summary page generating portion to generate a summary page having listed thereon identification information for identification of each of said one or more processes defined by said corresponding workflow generated by said workflow generating portion; a display control portion to control display of the help document generated, and a details page generating portion to read one or more help information items corresponding respectively to the one or more processes defined by the generated workflow to generate one or more details pages respectively including the one or more help information items read; and an associating portion to associate identification information items of the one or more processes included in the summary page with the one or more details pages generated, wherein the display control portion, in a case where any one of the identification information items of the one or more processes included in the summary page is designated, displays the details page associated with the identification information items designated. 10. The image processing apparatus according to claim 1 , wherein the display control portion displays the summary page in response to an instruction from a user.
| 0.894668 |
6,159,411 | 1 | 8 |
1. A stereolithographic method of forming a three-dimensional object from a plurality of adhered laminae by exposing successive layers of a material to prescribed stimulation, comprising: providing data representing an object to be formed; providing answers to a series of questions, including answers to stereolithographic machine type, recoating device, material type, and data file units; automatically determining a group of styles to be used in forming the object, wherein the determination is derived based on the answers provided, the styles including build styles and support styles; forming a layer of material according to at least one of the styles of the group, wherein the layer is formed in preparation for forming a successive lamina of the object, the layer in the object being formed according to at least one selected build style that includes geometric features; exposing the material to the prescribed stimulation to form a successive lamina of the object, wherein the exposure is performed according to at least one of the styles of the group; and repeating the acts of forming and exposing a plurality of times in order to form the object from a plurality of laminae.
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1. A stereolithographic method of forming a three-dimensional object from a plurality of adhered laminae by exposing successive layers of a material to prescribed stimulation, comprising: providing data representing an object to be formed; providing answers to a series of questions, including answers to stereolithographic machine type, recoating device, material type, and data file units; automatically determining a group of styles to be used in forming the object, wherein the determination is derived based on the answers provided, the styles including build styles and support styles; forming a layer of material according to at least one of the styles of the group, wherein the layer is formed in preparation for forming a successive lamina of the object, the layer in the object being formed according to at least one selected build style that includes geometric features; exposing the material to the prescribed stimulation to form a successive lamina of the object, wherein the exposure is performed according to at least one of the styles of the group; and repeating the acts of forming and exposing a plurality of times in order to form the object from a plurality of laminae. 8. The method of claim 1 wherein the answers comprise indicating the recoater type from a list of possibilities that are compatible with any previously answered questions.
| 0.559278 |
8,211,155 | 12 | 15 |
12. A dynamic pedicle screw comprising: a bone screw having a longitudinal axis, a proximal end and a distal end; the distal end of the bone screw having suitable surface texture and adapted to engage a vertebra; a housing at the proximal end of the bone screw; a bore in the housing aligned with the longitudinal axis of the bone screw, the bore having an open end and a closed end, the closed end of the bore terminating in a spherical pocket; an elongated deflectable post having a ball-shaped retainer at a first end; the deflectable post being positioned in the bore of the housing such that the ball-shaped retainer is positioned within the spherical pocket and a second end of the deflectable post extends through the open end of the bore coaxial to the longitudinal axis of the screw; and a compliant sleeve positioned within the bore between the deflectable post and the housing; and wherein the compliant sleeve is shaped to control deflection of the deflectable post from alignment with the longitudinal axis of the bone screw.
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12. A dynamic pedicle screw comprising: a bone screw having a longitudinal axis, a proximal end and a distal end; the distal end of the bone screw having suitable surface texture and adapted to engage a vertebra; a housing at the proximal end of the bone screw; a bore in the housing aligned with the longitudinal axis of the bone screw, the bore having an open end and a closed end, the closed end of the bore terminating in a spherical pocket; an elongated deflectable post having a ball-shaped retainer at a first end; the deflectable post being positioned in the bore of the housing such that the ball-shaped retainer is positioned within the spherical pocket and a second end of the deflectable post extends through the open end of the bore coaxial to the longitudinal axis of the screw; and a compliant sleeve positioned within the bore between the deflectable post and the housing; and wherein the compliant sleeve is shaped to control deflection of the deflectable post from alignment with the longitudinal axis of the bone screw. 15. The dynamic pedicle screw of claim 12 , wherein: said housing is associated with a limit surface positioned to contact the deflectable post after a predetermined amount of deflection of the deflectable post away from alignment with the longitudinal axis of the bone screw; and wherein the compliant sleeve has a polymer tube having an external diameter equal to the bore of the housing and an internal lumen having a diameter equal to a diameter of the deflectable post wherein the polymer tube flares out at an end of the compliant sleeve furthest from the ball-shaped retainer.
| 0.537302 |
7,893,850 | 14 | 18 |
14. An apparatus comprising: a reduced keyboard including a <NEXT> input member; a display configured to display a visual indicator having an appearance associated with the <NEXT> input member; a memory comprising a plurality of objects and a routine, the routine configured to: receive ambiguous data from the reduced keyboard wherein the <NEXT> input member is used for selection among a number of potential objects, wherein each potential object comprises an alternative variant output corresponding to the ambiguous data; and detect a plurality of selection inputs from the <NEXT> input member, each said selection input successively selecting a different potential object in a variant output.
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14. An apparatus comprising: a reduced keyboard including a <NEXT> input member; a display configured to display a visual indicator having an appearance associated with the <NEXT> input member; a memory comprising a plurality of objects and a routine, the routine configured to: receive ambiguous data from the reduced keyboard wherein the <NEXT> input member is used for selection among a number of potential objects, wherein each potential object comprises an alternative variant output corresponding to the ambiguous data; and detect a plurality of selection inputs from the <NEXT> input member, each said selection input successively selecting a different potential object in a variant output. 18. The apparatus of claim 14 wherein the reduced keyboard is configured to include the <NEXT> input member substantially adjacent another input member, and wherein the apparatus includes the thumbwheel at a location spaced from the <NEXT> input member and the another input member.
| 0.5 |
9,043,285 | 2 | 8 |
2. A system comprising: at least one processor; and a data classification system implemented by the at least one processor and including: an online module configured to: receive text data items; receive a set of classes into which the text data items are to be classified; select a phrase-based classifier to classify the text data items into the set of classes; and apply the phrase-based classifier to classify the text data items into the classes, the applying including: receiving a set of classes into which text data items are to be classified; creating a controlled vocabulary pertaining to classifying the text data items into the set of classes; building phrases based on the text data items and the controlled vocabulary; and classifying the text data items into the set of classes based on the phrases; and reclassifying a text data item of the text data items into the set of classes based on a consistency error.
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2. A system comprising: at least one processor; and a data classification system implemented by the at least one processor and including: an online module configured to: receive text data items; receive a set of classes into which the text data items are to be classified; select a phrase-based classifier to classify the text data items into the set of classes; and apply the phrase-based classifier to classify the text data items into the classes, the applying including: receiving a set of classes into which text data items are to be classified; creating a controlled vocabulary pertaining to classifying the text data items into the set of classes; building phrases based on the text data items and the controlled vocabulary; and classifying the text data items into the set of classes based on the phrases; and reclassifying a text data item of the text data items into the set of classes based on a consistency error. 8. The system of claim 2 , further comprising evaluating a precision of the classifying of the text data items.
| 0.743056 |
7,870,134 | 1 | 7 |
1. A method of clustering documents in terms of similarity within a node-based, distributed computing environment, comprising the steps of: inputting a plurality of documents; preprocessing the documents by assigning values representative of attributes associated with the documents; assigning an agent (DAg) to each document, each DAg being operative to compare the values assigned to the DAg's document with the values assigned to other documents to determine whether the DAg's document should be clustered at a current node because the DAg's document is similar to documents at the current node, or whether the DAg's document should be moved and clustered with documents at another node; assigning an agent (SAg) to each node, each SAg being operative to manage resources within the computing environment as the DAgs cluster the documents at the nodes; and displaying the results of the clustering to a user through a graphical user interface (GUI).
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1. A method of clustering documents in terms of similarity within a node-based, distributed computing environment, comprising the steps of: inputting a plurality of documents; preprocessing the documents by assigning values representative of attributes associated with the documents; assigning an agent (DAg) to each document, each DAg being operative to compare the values assigned to the DAg's document with the values assigned to other documents to determine whether the DAg's document should be clustered at a current node because the DAg's document is similar to documents at the current node, or whether the DAg's document should be moved and clustered with documents at another node; assigning an agent (SAg) to each node, each SAg being operative to manage resources within the computing environment as the DAgs cluster the documents at the nodes; and displaying the results of the clustering to a user through a graphical user interface (GUI). 7. The method of claim 1 , including the step of preprocessing documents and assigning values representative of their similarity.
| 0.777586 |
9,081,626 | 11 | 12 |
11. The method of claim 1 : wherein the source code written in the first assembly language is input from a first source code file, the method further comprising outputting the source code written in the second assembly language to a second source code file.
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11. The method of claim 1 : wherein the source code written in the first assembly language is input from a first source code file, the method further comprising outputting the source code written in the second assembly language to a second source code file. 12. The method of claim 11 : wherein the source code written in the first assembly language is input from multiple first source code files, and wherein the source code written in the second assembly language is output into multiple second source code files.
| 0.5 |
8,818,926 | 10 | 15 |
10. A computerized method for creating chat bot content, comprising the steps: getting a reduction matcher and a pattern matcher from another AIML chat bot; parsing a conversation script into query-response pairs with a query sentence and a response sentence; for each of the query-response pairs, using said reduction matcher to canonicalize said query sentence, and using said pattern matcher to find a pattern that matches the canonicalized query response; building an AIML list of the patterns coupled with the response sentences; and creating a new chat bot by combining said AIML list with said reduction matcher.
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10. A computerized method for creating chat bot content, comprising the steps: getting a reduction matcher and a pattern matcher from another AIML chat bot; parsing a conversation script into query-response pairs with a query sentence and a response sentence; for each of the query-response pairs, using said reduction matcher to canonicalize said query sentence, and using said pattern matcher to find a pattern that matches the canonicalized query response; building an AIML list of the patterns coupled with the response sentences; and creating a new chat bot by combining said AIML list with said reduction matcher. 15. The method of claim 10 , further comprising serving context-sensitive ads in real time.
| 0.835145 |
8,526,739 | 30 | 47 |
30. A method, comprising: receiving an image of a document; performing optical character recognition (OCR) on the image of the document; extracting an address of a sender of the document from the image based on the OCR; comparing the extracted address with content in a first database; identifying complementary textual information in a second database based on the address; and at least one of: extracting additional content from the image of the document; correcting OCR errors in the document using the complementary textual information, and normalizing data from the document prior to determining a validity of the document using at least one of the complementary textual information and predefined business rules.
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30. A method, comprising: receiving an image of a document; performing optical character recognition (OCR) on the image of the document; extracting an address of a sender of the document from the image based on the OCR; comparing the extracted address with content in a first database; identifying complementary textual information in a second database based on the address; and at least one of: extracting additional content from the image of the document; correcting OCR errors in the document using the complementary textual information, and normalizing data from the document prior to determining a validity of the document using at least one of the complementary textual information and predefined business rules. 47. The method as recited in claim 30 , wherein extracting the additional content comprises template-based extraction.
| 0.63125 |
7,519,564 | 1 | 8 |
1. A system that predicts and outputs events identified as being surprising to a person, comprising a memory having stored therein computer executable components and a processor that executes the following computer executable components: an interface component that receives contextual and historical data; a predictive model component that utilizes the contextual and historical data to predict an event and outputs the prediction if the prediction corresponds to one or more definitions of surprise, wherein the prediction corresponds to one or more definitions of surprise based on a probability of occurrence of the event, and wherein the predictive model component comprises: a robust predictive model that generates a prediction of the event based on interdependencies between variables associated with the contextual and historical data, wherein the interdependencies are not contemplated by the person; and a user expectancy model that utilizes the contextual and historical data to generate a prediction of the event based on, at least in part, machine learning and a case library that includes a plurality of surprising events and observations associated with the plurality of surprising events; a difference analyzer component that calculates a measure of difference between the prediction made by the robust predictive model and the prediction made by the user expectancy model to determine whether an event is surprising; and an alerting component that alerts the person of the surprising event upon the determination that the event is surprising.
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1. A system that predicts and outputs events identified as being surprising to a person, comprising a memory having stored therein computer executable components and a processor that executes the following computer executable components: an interface component that receives contextual and historical data; a predictive model component that utilizes the contextual and historical data to predict an event and outputs the prediction if the prediction corresponds to one or more definitions of surprise, wherein the prediction corresponds to one or more definitions of surprise based on a probability of occurrence of the event, and wherein the predictive model component comprises: a robust predictive model that generates a prediction of the event based on interdependencies between variables associated with the contextual and historical data, wherein the interdependencies are not contemplated by the person; and a user expectancy model that utilizes the contextual and historical data to generate a prediction of the event based on, at least in part, machine learning and a case library that includes a plurality of surprising events and observations associated with the plurality of surprising events; a difference analyzer component that calculates a measure of difference between the prediction made by the robust predictive model and the prediction made by the user expectancy model to determine whether an event is surprising; and an alerting component that alerts the person of the surprising event upon the determination that the event is surprising. 8. The system of claim 1 , further comprising a suggestion component that outputs suggestions of actions the person can perform in response to the predicted event.
| 0.852087 |
7,979,363 | 13 | 16 |
13. A computer implemented method for estimating an a priori probability of a class-of-interest in an input-data-set and for estimating a classification error for an adaptive Bayes classifier in classifying unlabeled patterns from an input-data-set into two classes, a class-of-interest or a class-other, comprising the steps of: a computer to perform; receiving a training set of patterns from said class-of-interest, a set of unlabeled patterns from said input-data-set, and a plurality of predetermined of class-of-interest weights with each said class-weight having different predetermined values; and selecting a predetermined number of Gaussian kernel densities functions; and selecting parameter values for said Gaussian kernel densities functions where said selected parameter values cause said Gaussian kernel densities to approximate an unknown input-data-set probability density function; and executing a training stage using first of said class-of-interest weights, said training set of patterns from said class-of-interest, and said unlabeled patterns from said input-data-set, including a step of least squares approximation of a weighted class-of-interest posterior probability function using a linear combination of weighted said Gaussian kernel density functions, with said training stage repeated to provide said weighted class-of-interest posterior probability functions for each of the remaining said class-of-interest weights; and classifying said patterns from said class-of-interest and said input-data-set into two classes, said class-of-interest or said class-other, in accordance with a conditional test defined by an adaptive Bayes decision rule using first of said weighted class-of-interest posterior probability functions, with said classification repeated using said conditional test defined by said adaptive Bayes decision rule for all remaining said weighted class-of-interest posterior probability functions; and minimizing a least squares criteria to find a plurality of values for class-other probabilities of correct classification that provide identical estimates of said class-of-interest a priori probability; and calculating a value for said class-of-interest a priori probability in said input-data-set using one of said values of said class-other probabilities of correct classification that minimized said least squares criteria, and classifying said patterns from said class-of-interest and said input-data-set into two classes, said class-of-interest or said class-other, using said calculated value of said class-of-interest a priori probability and said conditional test defined by said adaptive Bayes decision rule; and calculating a value for said class-other probability of correct classification from results obtained from said classification of patterns from said class-of-interest and said input-data-set into two classes, said class-of-interest or said class-other, using said conditional test defined by said adaptive Bayes decision rule and said calculated class-of-interest a priori probability; and calculating a value for a probability of error for said adaptive Bayes classifier in classifying patterns from said input-data-set into two classes, said class-of-interest or said class-other, using said calculated value of said class-of-interest a priori probability and said calculated value of said class-other probability of correct classification; and wherein said class-of-interest a priori probability in said input-data-set is estimated and said probability of error for said adaptive Bayes classifier in classifying said input-data-set is estimated using only labeled patterns from said class-of-interest training set, and said unlabeled patterns from said input-data-set, and without any a priori knowledge of said class-other.
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13. A computer implemented method for estimating an a priori probability of a class-of-interest in an input-data-set and for estimating a classification error for an adaptive Bayes classifier in classifying unlabeled patterns from an input-data-set into two classes, a class-of-interest or a class-other, comprising the steps of: a computer to perform; receiving a training set of patterns from said class-of-interest, a set of unlabeled patterns from said input-data-set, and a plurality of predetermined of class-of-interest weights with each said class-weight having different predetermined values; and selecting a predetermined number of Gaussian kernel densities functions; and selecting parameter values for said Gaussian kernel densities functions where said selected parameter values cause said Gaussian kernel densities to approximate an unknown input-data-set probability density function; and executing a training stage using first of said class-of-interest weights, said training set of patterns from said class-of-interest, and said unlabeled patterns from said input-data-set, including a step of least squares approximation of a weighted class-of-interest posterior probability function using a linear combination of weighted said Gaussian kernel density functions, with said training stage repeated to provide said weighted class-of-interest posterior probability functions for each of the remaining said class-of-interest weights; and classifying said patterns from said class-of-interest and said input-data-set into two classes, said class-of-interest or said class-other, in accordance with a conditional test defined by an adaptive Bayes decision rule using first of said weighted class-of-interest posterior probability functions, with said classification repeated using said conditional test defined by said adaptive Bayes decision rule for all remaining said weighted class-of-interest posterior probability functions; and minimizing a least squares criteria to find a plurality of values for class-other probabilities of correct classification that provide identical estimates of said class-of-interest a priori probability; and calculating a value for said class-of-interest a priori probability in said input-data-set using one of said values of said class-other probabilities of correct classification that minimized said least squares criteria, and classifying said patterns from said class-of-interest and said input-data-set into two classes, said class-of-interest or said class-other, using said calculated value of said class-of-interest a priori probability and said conditional test defined by said adaptive Bayes decision rule; and calculating a value for said class-other probability of correct classification from results obtained from said classification of patterns from said class-of-interest and said input-data-set into two classes, said class-of-interest or said class-other, using said conditional test defined by said adaptive Bayes decision rule and said calculated class-of-interest a priori probability; and calculating a value for a probability of error for said adaptive Bayes classifier in classifying patterns from said input-data-set into two classes, said class-of-interest or said class-other, using said calculated value of said class-of-interest a priori probability and said calculated value of said class-other probability of correct classification; and wherein said class-of-interest a priori probability in said input-data-set is estimated and said probability of error for said adaptive Bayes classifier in classifying said input-data-set is estimated using only labeled patterns from said class-of-interest training set, and said unlabeled patterns from said input-data-set, and without any a priori knowledge of said class-other. 16. The method of claim 13 wherein said step of executing said training stage includes a step of providing a plurality of said weights for each said Gaussian kernel density function.
| 0.945015 |
8,560,317 | 5 | 7 |
5. The voice recognition apparatus according to claim 1 , further comprising a use frequency managing unit for monitoring the number of uses of each of the plurality of words stored in the vocabulary dictionary storing unit and calculating a use frequency of each of the plurality of words, a use frequency storing unit for storing, as use frequency data, the use frequency calculated by the use frequency managing unit so as to correspond to each of the plurality of . words stored in the vocabulary dictionary storing unit, and a scale information managing unit for updating the scale information stored in the scale information storing unit using at least the use frequency data stored in the use frequency storing unit.
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5. The voice recognition apparatus according to claim 1 , further comprising a use frequency managing unit for monitoring the number of uses of each of the plurality of words stored in the vocabulary dictionary storing unit and calculating a use frequency of each of the plurality of words, a use frequency storing unit for storing, as use frequency data, the use frequency calculated by the use frequency managing unit so as to correspond to each of the plurality of . words stored in the vocabulary dictionary storing unit, and a scale information managing unit for updating the scale information stored in the scale information storing unit using at least the use frequency data stored in the use frequency storing unit. 7. The voice recognition apparatus according to claim 5 , further comprising a vocabulary group use frequency managing unit for dividing the plurality of words stored in the vocabulary dictionary storing unit into a plurality of vocabulary groups and calculating a use frequency of each of the vocabulary groups based on the use frequency of each of the plurality of words belonging to the vocabulary group stored in the vocabulary dictionary storing unit, a vocabulary group use frequency storing unit for storing, as vocabulary group use frequency data, the use frequency of the vocabulary group calculated by the vocabulary group use frequency managing unit so as to correspond to each of the vocabulary groups, and a threshold storing unit for storing a threshold indicating a criterion of the vocabulary group use frequency data at the time of extracting the recognition target words, wherein the vocabulary dictionary managing unit selectively performs one of operations (3) and (4) below referring to the threshold stored in the threshold storing unit and the vocabulary group use frequency data stored in the vocabulary group use frequency storing unit according to the extraction criterion information stored in the extraction criterion information storing unit: (3) for the vocabulary group whose vocabulary group use frequency data are equal to or larger than the threshold, the vocabulary dictionary managing unit extracts all the words belonging to this vocabulary group as the recognition target words regardless of the scale information, (4) for the vocabulary group whose vocabulary group use frequency data are smaller than the threshold, the vocabulary dictionary managing unit extracts the recognition target words from the words belonging to this vocabulary group based on the scale information.
| 0.5 |
10,109,278 | 11 | 18 |
11. A system for aligning content, the system comprising: an electronic data store configured to store: a transcription of an item of content comprising audio content; and a companion item of textual content, wherein the companion item of textual content comprises: a plurality of paragraphs of body text, and matter other than body text; and a physical computing device in communication with the electronic data store, the physical computing device configured to: identify, in the transcription, a portion of the transcription that includes text also included in a portion of the companion item of textual content; determine a level of correlation between words in the portion of the companion item of textual content and words in the portion of the transcription; determine that the level of correlation satisfies a threshold value; in response to determining that the level of correlation satisfies a threshold value, identify the portion of the companion item of content as body text; identify a second portion of the companion item of textual content that does not satisfy the threshold value with respect to any portion of the transcription; determine that the second portion of the companion item of textual content that does not satisfy the threshold value is back matter based at least in part on a determination that the second portion of the companion item of textual content that does not satisfy the threshold value appears within the companion item of textual content after a last portion of the companion item of textual content for which a corresponding portion of the transcription is identified; and generate content synchronization information that identifies (a) portions of the audio content that correspond to body text of the companion item of textual content and (b) further identifies the matter other than body text in the companion item, wherein the content synchronization information indicates that the matter other than body text in the companion item does not correspond to the audio content, wherein the matter other than body text includes the second portion of the companion item of textual content determined to be back matter, wherein the content synchronization information indicates that the portion of the companion item of textual content, excluding the matter other than body text, should be presented in synchronization with a portion of the audio content that corresponds to the portion of the transcription.
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11. A system for aligning content, the system comprising: an electronic data store configured to store: a transcription of an item of content comprising audio content; and a companion item of textual content, wherein the companion item of textual content comprises: a plurality of paragraphs of body text, and matter other than body text; and a physical computing device in communication with the electronic data store, the physical computing device configured to: identify, in the transcription, a portion of the transcription that includes text also included in a portion of the companion item of textual content; determine a level of correlation between words in the portion of the companion item of textual content and words in the portion of the transcription; determine that the level of correlation satisfies a threshold value; in response to determining that the level of correlation satisfies a threshold value, identify the portion of the companion item of content as body text; identify a second portion of the companion item of textual content that does not satisfy the threshold value with respect to any portion of the transcription; determine that the second portion of the companion item of textual content that does not satisfy the threshold value is back matter based at least in part on a determination that the second portion of the companion item of textual content that does not satisfy the threshold value appears within the companion item of textual content after a last portion of the companion item of textual content for which a corresponding portion of the transcription is identified; and generate content synchronization information that identifies (a) portions of the audio content that correspond to body text of the companion item of textual content and (b) further identifies the matter other than body text in the companion item, wherein the content synchronization information indicates that the matter other than body text in the companion item does not correspond to the audio content, wherein the matter other than body text includes the second portion of the companion item of textual content determined to be back matter, wherein the content synchronization information indicates that the portion of the companion item of textual content, excluding the matter other than body text, should be presented in synchronization with a portion of the audio content that corresponds to the portion of the transcription. 18. The system of claim 11 , wherein the physical computing device is further configured to determine the level of correlation between words in the portion of the companion item of textual content and words in the portion of the transcription by computing a correlation measure for a block of the companion item of textual content with respect to the transcription, the block comprising one or more portions of the companion item of textual content.
| 0.5 |
9,280,326 | 13 | 18 |
13. A computer implemented method for generating compiler code selector rules from an architecture description, the compiler code selector rules for use in a compiler that translates source code into machine instructions of a target processor, the method comprising: generating a plurality of semantic statements from semantic information included in a target processor architecture model of a target processor, the target processor architecture model described in a processor architecture description language, said semantic information describing an instruction set, wherein said target processor architecture model comprises semantic information and syntax information for the machine instructions, and description of non-terminals of the target processor; associating assembly syntax with semantic information; applying, to said semantic information, at least one semantic transformation from a library of pre-defined semantic transformations to generate a single semantic statement from a sequence of at least two of said plurality of semantic statements; accessing basic rules having tree patterns that map from source code operations to semantic patterns; permuting said basic rules based on said non-terminals to form set of permuted mapping rules; and matching semantic patterns of said permuted mapping rules to said semantic statements to form a description of said complier code selector rules comprising mappings from source code operations to associated assembly syntax; and mapping a sequence of two or more source code operations to a single machine instruction based on the accessed rules that matches from semantic statements to semantic patterns.
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13. A computer implemented method for generating compiler code selector rules from an architecture description, the compiler code selector rules for use in a compiler that translates source code into machine instructions of a target processor, the method comprising: generating a plurality of semantic statements from semantic information included in a target processor architecture model of a target processor, the target processor architecture model described in a processor architecture description language, said semantic information describing an instruction set, wherein said target processor architecture model comprises semantic information and syntax information for the machine instructions, and description of non-terminals of the target processor; associating assembly syntax with semantic information; applying, to said semantic information, at least one semantic transformation from a library of pre-defined semantic transformations to generate a single semantic statement from a sequence of at least two of said plurality of semantic statements; accessing basic rules having tree patterns that map from source code operations to semantic patterns; permuting said basic rules based on said non-terminals to form set of permuted mapping rules; and matching semantic patterns of said permuted mapping rules to said semantic statements to form a description of said complier code selector rules comprising mappings from source code operations to associated assembly syntax; and mapping a sequence of two or more source code operations to a single machine instruction based on the accessed rules that matches from semantic statements to semantic patterns. 18. The method of claim 13 , further comprising inputting a compiler description comprising said description of compiler code selector rules to an automatic compiler generation tool to automatically generate a compiler adapted to said target processor architecture.
| 0.5 |
9,183,250 | 1 | 4 |
1. A method, comprising: tracking queries and selections of search results in response to the queries; receiving a query that comprises a search term; identifying a plurality of different categories indicating different meanings associated with the search term; identifying from the tracked queries, one or more previous queries that include the search term; identifying one or more search results previously selected in response to the identified one or more previous queries that include the search term; identifying, from the one or more search results previously selected, search results selected most often in response to the identified one or more previous queries that include the search term; determining, using at least one processor and without user input, one or more categories of the plurality of different categories corresponding to the search results selected most often in response to the identified one or more previous queries that include the search term; identifying a plurality of search results responsive to the query; prioritizing search results, from the plurality of search results, associated with the one or more categories; and providing the prioritized search results to a user.
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1. A method, comprising: tracking queries and selections of search results in response to the queries; receiving a query that comprises a search term; identifying a plurality of different categories indicating different meanings associated with the search term; identifying from the tracked queries, one or more previous queries that include the search term; identifying one or more search results previously selected in response to the identified one or more previous queries that include the search term; identifying, from the one or more search results previously selected, search results selected most often in response to the identified one or more previous queries that include the search term; determining, using at least one processor and without user input, one or more categories of the plurality of different categories corresponding to the search results selected most often in response to the identified one or more previous queries that include the search term; identifying a plurality of search results responsive to the query; prioritizing search results, from the plurality of search results, associated with the one or more categories; and providing the prioritized search results to a user. 4. The method as recited in claim 1 , wherein determining the one or more categories from among the plurality of different categories corresponding to the search results selected most often comprises matching the search term to one or more popular queries of the tracked queries.
| 0.645939 |
6,076,061 | 2 | 3 |
2. The speech recognition apparatus according to claim 1, wherein said changing means changes classes of recognition information to be used for the speech recognition in accordance with the viewpoint detected by said detecting means.
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2. The speech recognition apparatus according to claim 1, wherein said changing means changes classes of recognition information to be used for the speech recognition in accordance with the viewpoint detected by said detecting means. 3. The speech recognition apparatus according to claim 2, wherein said changing means sets a plurality of areas each of which is related to a different class of the recognition information, selects one of the plurality of areas in accordance with the viewpoint detected by said detecting means, and determines a class of the recognition information, related to the selected area, to be used in the speech recognition.
| 0.5 |
10,140,619 | 12 | 16 |
12. One or more non-transitory machine-readable media having machine-executable instructions configured to generating a dynamic creative for a plurality of individual interactions, comprising code for: providing a plurality of structures that are selectable from within a third party creation tool, wherein each of the plurality of structures is configured: to switch between a plurality of alternative selections when the creative is run, for graphically-manipulated insertion into the creative, and for integration into a script representing the creative, wherein the script is run on an end user device and the creative dynamically changes according to the plurality of alternative selections when run, locally, on a plurality of end user devices; receiving selection of a content group that correlates to the plurality of alternative selections; receiving selection of a target group comprising a plurality of attributes describing viewers of the creative; determining that a viewer of the creative is in the target group; selecting, after a user request, an alternative selection from the plurality of alternative selections based on the determination that the viewer of the creative is in the target group; processing the alternative selection with a structure from the plurality of structures to customize the creative to the alternative selection that is associated with the content group; receiving feedback, based on the plurality of individual interactions with the dynamic creative, on how the content group is being received by the target group; and modifying how often the plurality of alternative selections are presented in the script for the target group without regard to how the content group is being received by viewers.
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12. One or more non-transitory machine-readable media having machine-executable instructions configured to generating a dynamic creative for a plurality of individual interactions, comprising code for: providing a plurality of structures that are selectable from within a third party creation tool, wherein each of the plurality of structures is configured: to switch between a plurality of alternative selections when the creative is run, for graphically-manipulated insertion into the creative, and for integration into a script representing the creative, wherein the script is run on an end user device and the creative dynamically changes according to the plurality of alternative selections when run, locally, on a plurality of end user devices; receiving selection of a content group that correlates to the plurality of alternative selections; receiving selection of a target group comprising a plurality of attributes describing viewers of the creative; determining that a viewer of the creative is in the target group; selecting, after a user request, an alternative selection from the plurality of alternative selections based on the determination that the viewer of the creative is in the target group; processing the alternative selection with a structure from the plurality of structures to customize the creative to the alternative selection that is associated with the content group; receiving feedback, based on the plurality of individual interactions with the dynamic creative, on how the content group is being received by the target group; and modifying how often the plurality of alternative selections are presented in the script for the target group without regard to how the content group is being received by viewers. 16. One or more physical machine-readable media having machine-executable instructions configured to generating the dynamic creative as recited in claim 12 , wherein the content group defines a plurality of options that define the alternative selections.
| 0.625369 |
9,318,109 | 9 | 10 |
9. The system of claim 1 , further configured to generate a distribution over partial dialog states using sequence classification decoding operations to generate one or more hypothesis including a confidence score or probability for each hypothesis.
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9. The system of claim 1 , further configured to generate a distribution over partial dialog states using sequence classification decoding operations to generate one or more hypothesis including a confidence score or probability for each hypothesis. 10. The system of claim 9 , wherein the one or more hypothesis provides an estimate of a distribution over a partial dialog state space.
| 0.5 |
7,929,165 | 1 | 7 |
1. A method for controlling a printer in a networked environment utilizing printer usage statistics and document features to determine whether to print a document or portion of a document, wherein the networked environment includes a plurality of printers, devices permitting the submittal of print job requests, a print server, and a document repository, the method comprising: receiving a job request to print a document from a device on a network; obtaining said document in digital form from the document repository or placing said document in digital form; extracting document and page specific information from said document; and determining whether printing of said document or a portion of said document is necessary based on analysis of said document and page specific information, including: providing a list of past print requests using historical information provided for each of said plurality of printers stored in said repository of said networked environment, applying a first classifier to find similar documents, applying a second classifier for making a determination for whether printing of an electronic form of said document is necessary, and, providing alternatives for accessing a physical version of said document if said determination is that printing of the electronic form of said document is unnecessary, presenting document location options for accessing a previously printed version of said document.
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1. A method for controlling a printer in a networked environment utilizing printer usage statistics and document features to determine whether to print a document or portion of a document, wherein the networked environment includes a plurality of printers, devices permitting the submittal of print job requests, a print server, and a document repository, the method comprising: receiving a job request to print a document from a device on a network; obtaining said document in digital form from the document repository or placing said document in digital form; extracting document and page specific information from said document; and determining whether printing of said document or a portion of said document is necessary based on analysis of said document and page specific information, including: providing a list of past print requests using historical information provided for each of said plurality of printers stored in said repository of said networked environment, applying a first classifier to find similar documents, applying a second classifier for making a determination for whether printing of an electronic form of said document is necessary, and, providing alternatives for accessing a physical version of said document if said determination is that printing of the electronic form of said document is unnecessary, presenting document location options for accessing a previously printed version of said document. 7. The method for controlling a printer in a networked environment utilizing printer usage statistics and document features according to claim 1 , wherein determining whether printing of said document or a portion of said document is necessary comprises determining whether said document or a portion of said document was previously printed.
| 0.62854 |
9,830,362 | 11 | 12 |
11. The computer-implemented method of claim 8 , ranking the one or more ranked search results comprising: raising a ranking of an individual ranked search result when there is a match between a first character set character in the search string and a first character set character in the individual ranked search result; lowering the ranking of an individual ranked search result when there is not a match between a first character set character in the search string and a first character set character in the individual ranked search result; and leaving the ranking of an individual ranked search result unchanged when there is no first character set character in the search string.
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11. The computer-implemented method of claim 8 , ranking the one or more ranked search results comprising: raising a ranking of an individual ranked search result when there is a match between a first character set character in the search string and a first character set character in the individual ranked search result; lowering the ranking of an individual ranked search result when there is not a match between a first character set character in the search string and a first character set character in the individual ranked search result; and leaving the ranking of an individual ranked search result unchanged when there is no first character set character in the search string. 12. The computer-implemented method of claim 11 , ranking the one or more ranked search results further comprising: determining how many first character set characters in the search string and first character set characters in the individual ranked search result match; assigning a highest ranking to the individual ranked search result when all the first character set characters in the search string match with first character set characters in the individual ranked search result; and assigning a raised ranking, but not a highest ranking, to the individual ranked search result when some of the first character set characters in the search string match with first character set characters in the individual ranked search result.
| 0.5 |
9,063,971 | 15 | 20 |
15. A non-transitory machine-readable storage medium storing instructions which, when executed, cause a processing device to perform a operations comprising: receiving user information associated with a query for information in a lightweight directory access protocol (LDAP) repository, the query received in an abstraction format; determining a computing domain in view of the user information; retrieving, by a processing device, a configuration file associated with the computing domain, the configuration file comprising a mapping for the query between an abstraction format and a vendor specific format; and converting the query to the vendor specific format in view of the mapping in the configuration file.
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15. A non-transitory machine-readable storage medium storing instructions which, when executed, cause a processing device to perform a operations comprising: receiving user information associated with a query for information in a lightweight directory access protocol (LDAP) repository, the query received in an abstraction format; determining a computing domain in view of the user information; retrieving, by a processing device, a configuration file associated with the computing domain, the configuration file comprising a mapping for the query between an abstraction format and a vendor specific format; and converting the query to the vendor specific format in view of the mapping in the configuration file. 20. The non-transitory machine-readable storage medium of claim 15 , further comprising: determining whether a syntax of the query matches a vendor specific syntax for the computing domain; and if the syntax of the query does not match the vendor specific syntax, converting the syntax of the query to the vendor specific syntax in view of the mapping in the configuration file.
| 0.5625 |
8,909,655 | 4 | 5 |
4. The method of claim 1 wherein the determined historical click-through rates are for a first geographic region.
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4. The method of claim 1 wherein the determined historical click-through rates are for a first geographic region. 5. The method of claim 4 wherein adjusting the ranking of the first search result further comprises determining that a region from which the query is received is the first geographic region.
| 0.5 |
8,180,635 | 13 | 14 |
13. The speech recognition system of claim 12 , wherein the weighting factor is selected based on an amount of change in noise level across previous portions of the speech signal.
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13. The speech recognition system of claim 12 , wherein the weighting factor is selected based on an amount of change in noise level across previous portions of the speech signal. 14. The speech recognition system of claim 13 , wherein a first weighting factor is selected when the amount of change is less than a predetermined threshold and a second weighting factor is selected when the amount of change exceeds the predetermined threshold.
| 0.5 |
7,904,080 | 5 | 6 |
5. A method according to claim 1 , wherein said map comprises one or more layers stacked above one another, each of said layers being associated with, and being capable of displaying, a portion of said network data.
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5. A method according to claim 1 , wherein said map comprises one or more layers stacked above one another, each of said layers being associated with, and being capable of displaying, a portion of said network data. 6. A method according to claim 5 , wherein said icon, when repeatedly clicked, enables drill down between said one or more layers of said map.
| 0.535948 |
8,285,082 | 16 | 17 |
16. A system for selecting digital content related to a portion of a block of text, the system comprising: means for receiving an indication of one or more words included in the block of text for which related digital content is to be identified, wherein: the one or more words are not manually provided as search queries for digital content; the block of text is accessible via a web interface; and the digital content comprises still or moving digital images; means for segmenting the one or more words included in the block of text into one or more segments comprising phrases or individual words, wherein the segmenting includes automatically removing one or more phrases or individual words that are less likely to result in finding images; means for searching a database of digital content based on the one or more segmented phrases or individual words, wherein: the means for searching is coupled to the means for receiving; means for retrieving from the database one or more digital content items or identifiers associated with the one or more digital content items, wherein: the digital content items are related to the one or more segmented phrases or individual words; and the means for retrieving is coupled to the means for searching; means for determining whether a licensing agreement is active with respect to the one or more retrieved digital content items or identifiers associated with the one or more digital content items; means for providing the retrieved digital content items or identifiers to the user only if a licensing agreement is active with respect to the retrieved digital content items or identifiers, wherein the means for providing is coupled to the means for retrieving; means for receiving a selection of one or more of the provided digital content items or identifiers from the user, wherein the means for receiving is coupled to the means for providing; and means for associating for display or replay the one or more selected digital content items or the one or more digital content items associated with the one or more selected identifiers with the one or more words in the block of text, wherein: the means for associating is coupled to the means for receiving; and the block of text and the one or more selected digital content items are accessible via the web interface.
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16. A system for selecting digital content related to a portion of a block of text, the system comprising: means for receiving an indication of one or more words included in the block of text for which related digital content is to be identified, wherein: the one or more words are not manually provided as search queries for digital content; the block of text is accessible via a web interface; and the digital content comprises still or moving digital images; means for segmenting the one or more words included in the block of text into one or more segments comprising phrases or individual words, wherein the segmenting includes automatically removing one or more phrases or individual words that are less likely to result in finding images; means for searching a database of digital content based on the one or more segmented phrases or individual words, wherein: the means for searching is coupled to the means for receiving; means for retrieving from the database one or more digital content items or identifiers associated with the one or more digital content items, wherein: the digital content items are related to the one or more segmented phrases or individual words; and the means for retrieving is coupled to the means for searching; means for determining whether a licensing agreement is active with respect to the one or more retrieved digital content items or identifiers associated with the one or more digital content items; means for providing the retrieved digital content items or identifiers to the user only if a licensing agreement is active with respect to the retrieved digital content items or identifiers, wherein the means for providing is coupled to the means for retrieving; means for receiving a selection of one or more of the provided digital content items or identifiers from the user, wherein the means for receiving is coupled to the means for providing; and means for associating for display or replay the one or more selected digital content items or the one or more digital content items associated with the one or more selected identifiers with the one or more words in the block of text, wherein: the means for associating is coupled to the means for receiving; and the block of text and the one or more selected digital content items are accessible via the web interface. 17. The system of claim 16 wherein the block of text comprises a web log.
| 0.922505 |
7,606,425 | 1 | 15 |
1. A method of learning events contained within a video image sequence, the method comprising: providing a computing system that is configured to receive the image sequence, the computing system programmed to: provide a behavioral analysis engine that is configured to learn new events contained within the image sequence; initiate a training phase mode within the behavioral analysis engine and obtain a feature vector including one or more parameters relating to an object disposed within the image sequence; identify one or more clusters for at least some of the one or more parameters, at least some of the one or more clusters corresponding to possible event candidates; display an identifier for at least some of the possible event candidates on a display; and allow a user to select one or more of the possible event candidates, and to include the selected one or more of the possible event candidates into an event library.
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1. A method of learning events contained within a video image sequence, the method comprising: providing a computing system that is configured to receive the image sequence, the computing system programmed to: provide a behavioral analysis engine that is configured to learn new events contained within the image sequence; initiate a training phase mode within the behavioral analysis engine and obtain a feature vector including one or more parameters relating to an object disposed within the image sequence; identify one or more clusters for at least some of the one or more parameters, at least some of the one or more clusters corresponding to possible event candidates; display an identifier for at least some of the possible event candidates on a display; and allow a user to select one or more of the possible event candidates, and to include the selected one or more of the possible event candidates into an event library. 15. The method of claim 1 , wherein said identifying step is performed using an unsupervised learning algorithm.
| 0.772358 |
8,214,372 | 15 | 16 |
15. The apparatus of claim 13 , wherein: the candidate set of configuration dependencies comprises a plurality of parameter and value strings; and the at least one processor is operative to rank-order by: analyzing the plurality of parameter and value strings, to estimate weighting statistics; computing weights for each of the configuration dependencies in the candidate set, based on the weighting statistics; and sorting the configuration dependencies in the candidate set in descending order of the weights to obtain the rank-ordered list.
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15. The apparatus of claim 13 , wherein: the candidate set of configuration dependencies comprises a plurality of parameter and value strings; and the at least one processor is operative to rank-order by: analyzing the plurality of parameter and value strings, to estimate weighting statistics; computing weights for each of the configuration dependencies in the candidate set, based on the weighting statistics; and sorting the configuration dependencies in the candidate set in descending order of the weights to obtain the rank-ordered list. 16. The apparatus of claim 15 , wherein: the at least one processor is operative to analyze the plurality of parameter and value strings using heuristics comprising: a different-valued dependency rank component; an infrequently-valued dependency rank component; and a parameter semantic distance rank component; and the at least one processor is operative to compute weights and sort the configuration dependencies by aggregating the different-valued dependency rank component, the infrequently-valued dependency rank component, and the parameter semantic distance rank component.
| 0.5 |
8,156,099 | 10 | 13 |
10. A computer-readable medium comprising: one or more instructions which, when executed by one or more processors, cause the one or more processors to receive, from a client device, a search query that includes a plurality of terms; one or more instructions which, when executed by the one or more processors, cause the one or more processors to determine a plurality of splits of the search query, where each of the plurality of splits separates the search query into a different plurality of partitions, where each of the plurality of partitions, in a split, includes one or more of the plurality of terms, and where a first partition, of the plurality of partitions, is associated with a geographic area; one or more instructions which, when executed by the one or more processors, cause the one or more processors to perform, for each of the plurality of splits, a search of a plurality of repositories to identify documents responsive to respective ones of the plurality of partitions in that split, where the plurality of repositories include a map data repository, and where the map data repository is searched to identify a location responsive to the first partition of the plurality of partitions; one or more instructions which, when executed by the one or more processors, cause the one or more processors to determine a respective confidence score for each of the plurality of splits based on scores associated with the documents identified for the plurality of partitions in that split; one or more instructions which, when executed by the one or more processors, cause the one or more processors to select a split, of the plurality of splits, based on the confidence scores for the plurality of splits; and one or more instructions which, when executed by the one or more processors, cause the one or more processors to transmit, to the client device, a listing of the documents identified for the plurality of partitions for the selected split, as search results for the search query.
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10. A computer-readable medium comprising: one or more instructions which, when executed by one or more processors, cause the one or more processors to receive, from a client device, a search query that includes a plurality of terms; one or more instructions which, when executed by the one or more processors, cause the one or more processors to determine a plurality of splits of the search query, where each of the plurality of splits separates the search query into a different plurality of partitions, where each of the plurality of partitions, in a split, includes one or more of the plurality of terms, and where a first partition, of the plurality of partitions, is associated with a geographic area; one or more instructions which, when executed by the one or more processors, cause the one or more processors to perform, for each of the plurality of splits, a search of a plurality of repositories to identify documents responsive to respective ones of the plurality of partitions in that split, where the plurality of repositories include a map data repository, and where the map data repository is searched to identify a location responsive to the first partition of the plurality of partitions; one or more instructions which, when executed by the one or more processors, cause the one or more processors to determine a respective confidence score for each of the plurality of splits based on scores associated with the documents identified for the plurality of partitions in that split; one or more instructions which, when executed by the one or more processors, cause the one or more processors to select a split, of the plurality of splits, based on the confidence scores for the plurality of splits; and one or more instructions which, when executed by the one or more processors, cause the one or more processors to transmit, to the client device, a listing of the documents identified for the plurality of partitions for the selected split, as search results for the search query. 13. The computer-readable medium of claim 10 , further comprising: one or more instructions to add, for one of plurality of splits, at least one additional term to one or more of the plurality of partitions in that split, where the at least one additional term is based on the context information.
| 0.589779 |
8,421,823 | 6 | 11 |
6. System comprising: a viewer video display; a processor coupled to the viewer video display; a camera communicating with the processor; the processor configured for executing logic on a computer readable storage medium to present on the display an emotion presentation user interface (UI), the UI including a first selector element selectable to cause an actual image of a viewer of the display as captured by a camera to be overlaid onto video, the UI including a second selector element selectable by a user to cause an emoticon to be overlaid onto video, the emoticon being established by the processor responsive to selection of the second selector element to match closely as possible the actual image of the viewer as captured by the camera and processed by the processor executing a recognition engine.
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6. System comprising: a viewer video display; a processor coupled to the viewer video display; a camera communicating with the processor; the processor configured for executing logic on a computer readable storage medium to present on the display an emotion presentation user interface (UI), the UI including a first selector element selectable to cause an actual image of a viewer of the display as captured by a camera to be overlaid onto video, the UI including a second selector element selectable by a user to cause an emoticon to be overlaid onto video, the emoticon being established by the processor responsive to selection of the second selector element to match closely as possible the actual image of the viewer as captured by the camera and processed by the processor executing a recognition engine. 11. The system of claim 6 , wherein the processor is further configured for presenting, along with the image of the viewer derived from the camera, audio generated by the viewer and captured by a microphone communicating with the processor.
| 0.651163 |
9,317,020 | 7 | 11 |
7. A method of defining a future release of a command library, comprising: receiving at a Web site requests to download an upgrade to a previously installed command library containing instructions for controlling the operation of one or more functions of an appliance to thereby provide a controlling device with a capability to command functions of the appliance which appliance was incapable of being commanded by the controlling device using the previously installed command library; and using statistics derived from information associated with the requests received at the Web site to determine if the future release of a command library is to include the capability to command the functions of the appliance which were incapable of being commanded by the controlling device using the previously installed command library.
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7. A method of defining a future release of a command library, comprising: receiving at a Web site requests to download an upgrade to a previously installed command library containing instructions for controlling the operation of one or more functions of an appliance to thereby provide a controlling device with a capability to command functions of the appliance which appliance was incapable of being commanded by the controlling device using the previously installed command library; and using statistics derived from information associated with the requests received at the Web site to determine if the future release of a command library is to include the capability to command the functions of the appliance which were incapable of being commanded by the controlling device using the previously installed command library. 11. The method as recited in claim 7 , wherein the information associated with the requests comprises information relevant to the appliance.
| 0.570552 |
9,189,531 | 9 | 15 |
9. The method of claim 1 , further comprising: mediating, by a computer, a plurality of ontologies.
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9. The method of claim 1 , further comprising: mediating, by a computer, a plurality of ontologies. 15. The method of claim 9 where mediating, by a computer, a plurality of ontologies comprises: storing, by a computer, source specific statistics and metadata describing the content of said database both qualitatively and quantitatively.
| 0.5 |
9,053,199 | 1 | 2 |
1. A computing device comprising: a web document accessor configured to access a web document, the web document having a uniform resource locator (URL) for a script file and a unique identifier for the script file appended to the URL, a parser configured to recognize the unique identifier and to obtain the unique identifier from the web document; a script file locator configured to use the unique identifier to determine whether the script file is located at a same server as that specified by the URL for the script file, or that the script file is located in a script file repository located at a different server from that specified by the URL for the script file, the script file repository comprising scripts for a plurality of different web documents; and a script file obtainer configured to obtain the script file from the script file repository when the script file locator determines the script file is located in the script file repository.
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1. A computing device comprising: a web document accessor configured to access a web document, the web document having a uniform resource locator (URL) for a script file and a unique identifier for the script file appended to the URL, a parser configured to recognize the unique identifier and to obtain the unique identifier from the web document; a script file locator configured to use the unique identifier to determine whether the script file is located at a same server as that specified by the URL for the script file, or that the script file is located in a script file repository located at a different server from that specified by the URL for the script file, the script file repository comprising scripts for a plurality of different web documents; and a script file obtainer configured to obtain the script file from the script file repository when the script file locator determines the script file is located in the script file repository. 2. A computing device according to claim 1 , further comprising a cache wherein the script file obtainer is further configured to obtain the script file associated with the unique identifier from the cache in response to a determination that the script file associated with the unique identifier has been previously obtained from the script file repository, and a copy is located in the cache.
| 0.617704 |
8,266,132 | 13 | 14 |
13. A system comprising the following computer-executable components: a text extractor component that extracts text from a digital image; a determiner component that automatically determines whether or not the digital image is a map of a geographic region, wherein the determiner component determines whether or not the digital image is a map of a geographic region by comparing the text extracted from the digital image with entries in a database of known points of interest in the geographic region to identify matches, and subsequently determining whether the matched text extracted from the digital image has a spatial correspondence with the known points of interest on a reference map; and a correlator component that generates correlation data that causes the digital image to be correlated with a portion of the reference map that pertains to the geographic region if the determiner component determines that the digital image is a map of the geographic region; wherein the text extractor component, the determiner component, and the correlator component are implemented on one or more processors.
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13. A system comprising the following computer-executable components: a text extractor component that extracts text from a digital image; a determiner component that automatically determines whether or not the digital image is a map of a geographic region, wherein the determiner component determines whether or not the digital image is a map of a geographic region by comparing the text extracted from the digital image with entries in a database of known points of interest in the geographic region to identify matches, and subsequently determining whether the matched text extracted from the digital image has a spatial correspondence with the known points of interest on a reference map; and a correlator component that generates correlation data that causes the digital image to be correlated with a portion of the reference map that pertains to the geographic region if the determiner component determines that the digital image is a map of the geographic region; wherein the text extractor component, the determiner component, and the correlator component are implemented on one or more processors. 14. The system of claim 13 , further comprising a display component that displays an indication on a computer display screen that the digital image is a map of the geographic region.
| 0.847059 |
9,536,069 | 1 | 3 |
1. A computer-implemented process of authenticating a user requesting access to protected resource using credentials that are personalized using formatting options, the process comprising: using a computing device to perform the steps of: capturing credentials from the user which are formatted using formatting options, wherein the credentials comprise one or more of formatted user name, formatted password or formatted numerical PIN, and wherein the formatting options comprise Font, Font Size, Font Color, Shading, Font Style, Font Effects, Font Underline, and character effects; comparing the captured formatted credentials against formatted credentials stored on a server that are designated by the user as valid credentials prior to requesting access; flagging the captured credentials as valid and allowing the user to have access when the comparison indicates that a match occurs; flagging the captured credentials as invalid and rejecting the request for access when the comparison indicates that a match does not occur; alerting the user via alert communication methods chosen by the user including email, text message, voice message, voice call, SMS, audible alarm, or visual clues; and logging the user request and the steps performed by the computing device.
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1. A computer-implemented process of authenticating a user requesting access to protected resource using credentials that are personalized using formatting options, the process comprising: using a computing device to perform the steps of: capturing credentials from the user which are formatted using formatting options, wherein the credentials comprise one or more of formatted user name, formatted password or formatted numerical PIN, and wherein the formatting options comprise Font, Font Size, Font Color, Shading, Font Style, Font Effects, Font Underline, and character effects; comparing the captured formatted credentials against formatted credentials stored on a server that are designated by the user as valid credentials prior to requesting access; flagging the captured credentials as valid and allowing the user to have access when the comparison indicates that a match occurs; flagging the captured credentials as invalid and rejecting the request for access when the comparison indicates that a match does not occur; alerting the user via alert communication methods chosen by the user including email, text message, voice message, voice call, SMS, audible alarm, or visual clues; and logging the user request and the steps performed by the computing device. 3. The process of claim 1 , where in wherein the valid credentials are set for each time range and time range is of duration of minutes, a day, days, week, weeks, month, years, day of week or time period of the day.
| 0.671254 |
10,025,487 | 1 | 9 |
1. A method comprising: detecting a location of a text selection icon on a display of an electronic device; detecting a touch input representing a selection of text displayed on the display using the text selection icon; determining a movement of the text selection icon while the touch input is maintained during the movement, wherein the movement is continuous and drags the text selection icon into a zone adjacent an edge of the display; in response to the determination, enabling a row by row selection mode; and during the movement of the text selection icon while the touch input is maintained and the row by row selection mode is enabled, dynamically increasing a width of said zone based on at least one of a number of rows of displayed text selected by the continuous movement of the text selection icon or a speed of the movement; wherein: if the detected location of the text selection icon is maintained within said zone during the movement while the touch input is maintained, the displayed text is selected on a row by row basis; and, if the detected location of the text selection icon moves outside said zone and moves into the displayed text during the movement while the touch input is maintained, the row by row selection mode is switched to a letter by letter selection mode, wherein in the letter by letter selection mode the displayed text is selected on a letter by letter basis.
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1. A method comprising: detecting a location of a text selection icon on a display of an electronic device; detecting a touch input representing a selection of text displayed on the display using the text selection icon; determining a movement of the text selection icon while the touch input is maintained during the movement, wherein the movement is continuous and drags the text selection icon into a zone adjacent an edge of the display; in response to the determination, enabling a row by row selection mode; and during the movement of the text selection icon while the touch input is maintained and the row by row selection mode is enabled, dynamically increasing a width of said zone based on at least one of a number of rows of displayed text selected by the continuous movement of the text selection icon or a speed of the movement; wherein: if the detected location of the text selection icon is maintained within said zone during the movement while the touch input is maintained, the displayed text is selected on a row by row basis; and, if the detected location of the text selection icon moves outside said zone and moves into the displayed text during the movement while the touch input is maintained, the row by row selection mode is switched to a letter by letter selection mode, wherein in the letter by letter selection mode the displayed text is selected on a letter by letter basis. 9. A method according to claim 1 , wherein the displayed text selected after the text selection icon moves outside said zone is selected on a letter by letter basis while the text selected on the row by row basis remains selected after the text selection icon moves outside said zone.
| 0.5 |
9,800,618 | 15 | 20 |
15. The non-transitory computer-readable medium of claim 14 , wherein the instructions further cause the processor to: process, via the user agent, an indication from an identity manager specifying the user identity determined to satisfy the security policy requirements; and cause the evaluation operation to evaluate, in accordance with the indication, the privacy preference of the user identity specified in the determination.
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15. The non-transitory computer-readable medium of claim 14 , wherein the instructions further cause the processor to: process, via the user agent, an indication from an identity manager specifying the user identity determined to satisfy the security policy requirements; and cause the evaluation operation to evaluate, in accordance with the indication, the privacy preference of the user identity specified in the determination. 20. The non-transitory computer-readable medium of claim 15 , wherein the instructions further cause the processor to determine an acceptability of the privacy policy, using the evaluation.
| 0.745283 |
9,519,678 | 7 | 12 |
7. A system for providing assertions regarding an item query, the system comprising: at least one data store configured to store assertions, wherein each assertion is representative of at least one search criterion, and wherein the at least one search criterion is determined based at least in part on a previous action of at least one user taken in response to results of a previously executed query, and wherein each assertion is selectable by an additional user to generate a new query based at least in part on modified set of search criteria corresponding to each assertion; and one or more processors in communication with the at least one data store, the one or more processors configured to: receive, from a user computing device, a query including search criteria; determine an assertion of the stored assertions that is relevant to the received query based at least in part on the search criteria; transmit, to the user computing device, a display page including results of the query and the assertion that is relevant to the query; receive a user selection of the assertion, wherein the user selection of the assertion corresponds to a user request to generate a new query based at least in part on modifying the search criteria included within the received query in accordance with the at least one search criterion represented by the assertion; generate the new query based at least in part on modifying the search criteria included within the received query in accordance with the at least one search criterion represented by the determined assertion; and transmit results of the new query to the user computing device.
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7. A system for providing assertions regarding an item query, the system comprising: at least one data store configured to store assertions, wherein each assertion is representative of at least one search criterion, and wherein the at least one search criterion is determined based at least in part on a previous action of at least one user taken in response to results of a previously executed query, and wherein each assertion is selectable by an additional user to generate a new query based at least in part on modified set of search criteria corresponding to each assertion; and one or more processors in communication with the at least one data store, the one or more processors configured to: receive, from a user computing device, a query including search criteria; determine an assertion of the stored assertions that is relevant to the received query based at least in part on the search criteria; transmit, to the user computing device, a display page including results of the query and the assertion that is relevant to the query; receive a user selection of the assertion, wherein the user selection of the assertion corresponds to a user request to generate a new query based at least in part on modifying the search criteria included within the received query in accordance with the at least one search criterion represented by the assertion; generate the new query based at least in part on modifying the search criteria included within the received query in accordance with the at least one search criterion represented by the determined assertion; and transmit results of the new query to the user computing device. 12. The system of claim 7 , wherein the categorization of the received query is further based at least in part on at least one of past activity of the user computing device, a user profile associated with the user computing device, or acquisition history of a user associated with the user computing device.
| 0.552478 |
8,539,359 | 1 | 65 |
1. A non-abstract machine system that is structured to automatically present as first presentations to a first user of the system, user-acceptable invitations to join in on telecommunications-mediated information exchange forums and/or to automatically present in the first presentations to the first user, user-acceptable suggestions of additional telecommunications-conveyed informational content to investigate, wherein the presented invitations and/or suggestions are based on content that the first user is presented with and are based on automatically repeated determinations by the machine system of what specific sub-portion or specific sub-portions of the presented content the first user more recently centered his or her attention upon, wherein the automatically repeated determinations regarding attention are carried out transparently by the machine system without need for diverted centering of attention by the user directed to aiding the automatically repeated transparent determinations by the machine system, the machine system comprising: a presentation format controller that determines or controls at least one of: whether or not a given user-acceptable invitation or user-acceptable suggestion is presented to the first user; when a given first presentation is presented; what order of presentation is used for multiple ones of the first presentations; at what rate multiple ones of the first presentations are automatically presented; and in what format are the given one or multiple ones of the first presentations automatically presented to the first user; wherein at least a portion of the machine system includes a data processing machine, and wherein said automatically determined and more recent centerings of attention by the first user occurred no more than at least one of: 3 hours prior to said presentation of the first presentations to the first user; and a determined time duration prior to said presentation of the first presentations to the first user, the determined time duration being determined based on a currently active profile characterizing the first user.
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1. A non-abstract machine system that is structured to automatically present as first presentations to a first user of the system, user-acceptable invitations to join in on telecommunications-mediated information exchange forums and/or to automatically present in the first presentations to the first user, user-acceptable suggestions of additional telecommunications-conveyed informational content to investigate, wherein the presented invitations and/or suggestions are based on content that the first user is presented with and are based on automatically repeated determinations by the machine system of what specific sub-portion or specific sub-portions of the presented content the first user more recently centered his or her attention upon, wherein the automatically repeated determinations regarding attention are carried out transparently by the machine system without need for diverted centering of attention by the user directed to aiding the automatically repeated transparent determinations by the machine system, the machine system comprising: a presentation format controller that determines or controls at least one of: whether or not a given user-acceptable invitation or user-acceptable suggestion is presented to the first user; when a given first presentation is presented; what order of presentation is used for multiple ones of the first presentations; at what rate multiple ones of the first presentations are automatically presented; and in what format are the given one or multiple ones of the first presentations automatically presented to the first user; wherein at least a portion of the machine system includes a data processing machine, and wherein said automatically determined and more recent centerings of attention by the first user occurred no more than at least one of: 3 hours prior to said presentation of the first presentations to the first user; and a determined time duration prior to said presentation of the first presentations to the first user, the determined time duration being determined based on a currently active profile characterizing the first user. 65. The machine system of claim 1 wherein: the invitations and/or suggestions are automatically successively presented over time to the first user; and the presentation format controller is configured to determine or control the rate at which the invitations and/or suggestions are successively presented as a function of at least one of: a determined mood of the first user; a predefined rate limit corresponding to a subscription level of the first user; a machine system determined, information pull rate at which Current focus indicating records (CFi's) of the first user are pulled; a rate at which advertisement sponsors decide to invite different kinds of users that are of interest to the advertisement sponsors to corresponding online forums; how on-topic the received invitations/suggestions appear to be relative to a topic that machine system determines the first user appears to currently have on his or her mind; how aged are potentially-to-be presented invitations and/or suggestions relative to when corresponding CFi data was sent out on behalf of the first user for generating the potentially-to-be presented invitations and/or suggestions; how quickly acceptance by the first user is needed for the received invitations and/or suggestions before the latter become stale; how busy a local presentation machine of the first user is with higher priority tasks or not; a rate of CFi's servicings that is susceptible to being curtailed due to bandwidth limitations at a CFi's servicing center; an actuation by the first user of faster-rate-requesting flag that indicates the first user wants to be provided with a greater number of new invitations per unit of time; an actuation by the first user of slower-rate-requesting flag that indicates the first user wants to be provided with a smaller number of new invitations per unit of time; and a previous rate at which new invitations were presented to the first user.
| 0.5 |
8,990,347 | 2 | 3 |
2. The method, as set forth in claim 1 , further comprising at least one of a generating and parsing said one or more identifiers and said one or more data request types from at least one input source.
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2. The method, as set forth in claim 1 , further comprising at least one of a generating and parsing said one or more identifiers and said one or more data request types from at least one input source. 3. The method, as set forth in claim 2 , wherein said at least one input source is from at least one of a data file, internet content, audio signal, closed caption text, activation of a hyperlink, network resource redirection, autosearch, resource identifier, and a user interface device.
| 0.786033 |
9,870,519 | 1 | 6 |
1. A method for hierarchical sparse dictionary learning (“HiSDL”) to construct a learned dictionary regularized by an a priori over-complete dictionary, comprising: providing at least one a priori over-complete dictionary for regularization; performing sparse coding of the at least one a priori over-complete dictionary to provide a sparse coded dictionary; using a processor, updating the sparse coded dictionary with regularization using auxiliary variables to provide a learned dictionary; determining whether the learned dictionary converges to an input data set; and outputting the learned dictionary regularized by the at least one a priori over-complete dictionary when the learned dictionary converges to the input data set.
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1. A method for hierarchical sparse dictionary learning (“HiSDL”) to construct a learned dictionary regularized by an a priori over-complete dictionary, comprising: providing at least one a priori over-complete dictionary for regularization; performing sparse coding of the at least one a priori over-complete dictionary to provide a sparse coded dictionary; using a processor, updating the sparse coded dictionary with regularization using auxiliary variables to provide a learned dictionary; determining whether the learned dictionary converges to an input data set; and outputting the learned dictionary regularized by the at least one a priori over-complete dictionary when the learned dictionary converges to the input data set. 6. The method of claim 1 , wherein performing the sparse coding of the at least one a priori over-complete dictionary includes using a Fast Iterative Shrinkage-Threshold (“FISTA”) approach for l 1 regularized least squares.
| 0.571154 |
8,856,143 | 3 | 4 |
3. The method of claim 1 , where the document includes a search query.
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3. The method of claim 1 , where the document includes a search query. 4. The method of claim 3 , further comprising: performing a local search of documents associated with the particular geographic region using the search query.
| 0.5 |
4,481,665 | 1 | 3 |
1. A method for facilitating the automatic recognition of optically scanned and read characters from within separate sequentially scanned blocks of written information, said method comprising the steps of: predetermining the classification of a first block of written information and a next successive block of written information of said separate sequentially scanned blocks according to the types of information contained therein; optically and sequentially scanning said separate blocks of information and generating a representative output signal for each of said characters; retrievally storing said output signals; reading each of the stored output signals in the order scanned and determining the end of said first block of information and the beginning of said next successive block of information; classifying each of the read output signals of said first block in accordance with the predetermined classification of said first block; and processing the output signals of said first block by a character recognition circuit for identifying the characters within said first block.
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1. A method for facilitating the automatic recognition of optically scanned and read characters from within separate sequentially scanned blocks of written information, said method comprising the steps of: predetermining the classification of a first block of written information and a next successive block of written information of said separate sequentially scanned blocks according to the types of information contained therein; optically and sequentially scanning said separate blocks of information and generating a representative output signal for each of said characters; retrievally storing said output signals; reading each of the stored output signals in the order scanned and determining the end of said first block of information and the beginning of said next successive block of information; classifying each of the read output signals of said first block in accordance with the predetermined classification of said first block; and processing the output signals of said first block by a character recognition circuit for identifying the characters within said first block. 3. The method of claim 1 wherein the step of determining the end of said first block of information and the beginning of said next successive blocks of information comprises comparing the gap length between adjacent characters to the average gap length of all characters.
| 0.61831 |
9,286,289 | 1 | 9 |
1. A computer system comprising at least one processor configured to transform a lexicon network stored in memory, the lexicon network comprising a plurality of nodes and a plurality of edges, wherein: each node of the lexicon network comprises a gloss of a lexicon entry of a natural language; each edge of the lexicon network comprises a direction and a weight; wherein creating the lexicon network comprises receiving an input indicative of a direction of an edge connecting a first node of the lexicon network to a second node of the lexicon network; wherein transforming the lexicon network comprises ordering the lexicon network by distributing the plurality of nodes among a plurality of levels, the plurality of levels arranged in an ordered sequence, so that all edges of the ordered lexicon network point in the same direction relative to the ordered sequence of levels; wherein ordering the lexicon network comprises assigning the first node of the lexicon network to a first level of the plurality of levels the first level selected according to the direction of the edge connecting the first and second nodes, and further according to a first penalty score determined for a first subset of edges of the lexicon network, the first subset of edges selected for removal from the lexicon network according to a tentative assignment of the first node to the first level, the first penalty score determined according to the weight of at least one edge of the first subset of edges, wherein the weight of the at least one of the first subset of edges is indicative of a semantic importance of the at least one of the first subset of edges compared to other edges of the lexicon network; and wherein the at least one processor is further configured to transmit at least part of the ordered lexicon network to a second computer system, wherein the second computer system is configured to: receive electronic natural language text, perform, via a word sense disambiguation engine, word sense disambiguation on the received electronic natural language text according to the at least part of the ordered lexicon network, and output a disambiguation indicator based on the word sense disambiguation to a computer-based application.
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1. A computer system comprising at least one processor configured to transform a lexicon network stored in memory, the lexicon network comprising a plurality of nodes and a plurality of edges, wherein: each node of the lexicon network comprises a gloss of a lexicon entry of a natural language; each edge of the lexicon network comprises a direction and a weight; wherein creating the lexicon network comprises receiving an input indicative of a direction of an edge connecting a first node of the lexicon network to a second node of the lexicon network; wherein transforming the lexicon network comprises ordering the lexicon network by distributing the plurality of nodes among a plurality of levels, the plurality of levels arranged in an ordered sequence, so that all edges of the ordered lexicon network point in the same direction relative to the ordered sequence of levels; wherein ordering the lexicon network comprises assigning the first node of the lexicon network to a first level of the plurality of levels the first level selected according to the direction of the edge connecting the first and second nodes, and further according to a first penalty score determined for a first subset of edges of the lexicon network, the first subset of edges selected for removal from the lexicon network according to a tentative assignment of the first node to the first level, the first penalty score determined according to the weight of at least one edge of the first subset of edges, wherein the weight of the at least one of the first subset of edges is indicative of a semantic importance of the at least one of the first subset of edges compared to other edges of the lexicon network; and wherein the at least one processor is further configured to transmit at least part of the ordered lexicon network to a second computer system, wherein the second computer system is configured to: receive electronic natural language text, perform, via a word sense disambiguation engine, word sense disambiguation on the received electronic natural language text according to the at least part of the ordered lexicon network, and output a disambiguation indicator based on the word sense disambiguation to a computer-based application. 9. The computer system of claim 1 , wherein each edge of the lexicon network points from a source gloss to a destination gloss, and wherein the each edge indicates that a token of the source gloss has a meaning defined by the destination gloss.
| 0.5 |
9,201,870 | 13 | 19 |
13. A method for maintaining a database of translated content, comprising: providing a database storing a plurality of source phrases in a source natural language dialect and a plurality of translated phrases, each of the plurality of translated phrases being a translation into a first target dialect of one of the plurality of source phrases; providing an application server that provides an application service comprising generating dynamic Web page content for Internet banking responsive to a Web page request from a user of a financial institution, wherein the dynamic Web page content comprises one or more phrases in the source natural language dialect; processing the dynamic Web page content into at least a first token and a second token, wherein the first token comprises a first source phrase and the second token comprises a second source phrase; determining the first token is translatable and the second token is non-translatable; identifying, based at least in part on determining the first token is translatable, that the first source phrase of the first token is a candidate phrase having a translatable component for addition to the database, said candidate phrase being one of the one or more phrases, and adding the translatable component of the candidate phrase to the plurality of source phrases, said steps of identifying and adding being performed by the application server; translating the first token, wherein the translatable component of the candidate phrase of the first token is translated into a translated component in the first target dialect; adding the translated component of the first token to the plurality of translated phrases in the database; determining the second token contains sensitive content based at least in part on the user, and performing security measures by replacing the second token with content-neutral text; determining whether the first source phrase is associated with a uniform resource identifier (URI), wherein the URI is associated with the Web page requested by the user; associating, by the one or more computers, the first source phrase to the URI if the first source phrase was not associated with the URI; determining the first target dialect is associated with a target language based at least in part on a location of the financial institution; determining a second dialect is associated with the target language; determining a plurality of second-dialect translated phrases, wherein each of the plurality of second-dialect translated phrases corresponds to a translation into the second dialect of one of the plurality of source phrases; determining one or more of the plurality of source phrases having a corresponding target-dialect translated phrase and a corresponding second-dialect translated phrase; selecting the corresponding target-dialect translated phrase baseed on the location of the financial institution; selecting the corresponding second-dialect translated phrase when no corresponding target-dialect translated phrase exists; and providing the translated dynamic Web page to the user of the financial institution.
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13. A method for maintaining a database of translated content, comprising: providing a database storing a plurality of source phrases in a source natural language dialect and a plurality of translated phrases, each of the plurality of translated phrases being a translation into a first target dialect of one of the plurality of source phrases; providing an application server that provides an application service comprising generating dynamic Web page content for Internet banking responsive to a Web page request from a user of a financial institution, wherein the dynamic Web page content comprises one or more phrases in the source natural language dialect; processing the dynamic Web page content into at least a first token and a second token, wherein the first token comprises a first source phrase and the second token comprises a second source phrase; determining the first token is translatable and the second token is non-translatable; identifying, based at least in part on determining the first token is translatable, that the first source phrase of the first token is a candidate phrase having a translatable component for addition to the database, said candidate phrase being one of the one or more phrases, and adding the translatable component of the candidate phrase to the plurality of source phrases, said steps of identifying and adding being performed by the application server; translating the first token, wherein the translatable component of the candidate phrase of the first token is translated into a translated component in the first target dialect; adding the translated component of the first token to the plurality of translated phrases in the database; determining the second token contains sensitive content based at least in part on the user, and performing security measures by replacing the second token with content-neutral text; determining whether the first source phrase is associated with a uniform resource identifier (URI), wherein the URI is associated with the Web page requested by the user; associating, by the one or more computers, the first source phrase to the URI if the first source phrase was not associated with the URI; determining the first target dialect is associated with a target language based at least in part on a location of the financial institution; determining a second dialect is associated with the target language; determining a plurality of second-dialect translated phrases, wherein each of the plurality of second-dialect translated phrases corresponds to a translation into the second dialect of one of the plurality of source phrases; determining one or more of the plurality of source phrases having a corresponding target-dialect translated phrase and a corresponding second-dialect translated phrase; selecting the corresponding target-dialect translated phrase baseed on the location of the financial institution; selecting the corresponding second-dialect translated phrase when no corresponding target-dialect translated phrase exists; and providing the translated dynamic Web page to the user of the financial institution. 19. The method of claim 13 wherein the translatable component comprises a pattern request.
| 0.858934 |
9,747,268 | 1 | 2 |
1. A computing device configured to: display an electronic message that includes a change made to a document, wherein the change is viewable within a body portion of the electronic message; receive a reply to the electronic message that includes a received change for the document, wherein the received change for the document is made directly from within the electronic message and is made outside of the document; and after receiving the reply to the electronic message, automatically incorporate the received change into the document.
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1. A computing device configured to: display an electronic message that includes a change made to a document, wherein the change is viewable within a body portion of the electronic message; receive a reply to the electronic message that includes a received change for the document, wherein the received change for the document is made directly from within the electronic message and is made outside of the document; and after receiving the reply to the electronic message, automatically incorporate the received change into the document. 2. The device of claim 1 , further configured to contain document changes within the electronic message.
| 0.75 |
8,024,372 | 15 | 21 |
15. A computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for constructing a model that generates text, the method comprising: representing a concept as a cluster node; representing a word as a terminal node; assigning a weight to a link between two nodes; and training the model based on a set of documents, comprising: for each cluster node, computing a probabilistic cost of a corresponding concept existing in a document but not triggering any words.
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15. A computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for constructing a model that generates text, the method comprising: representing a concept as a cluster node; representing a word as a terminal node; assigning a weight to a link between two nodes; and training the model based on a set of documents, comprising: for each cluster node, computing a probabilistic cost of a corresponding concept existing in a document but not triggering any words. 21. The computer-readable storage medium of claim 15 , wherein the method further comprises generating a new link between: a cluster node assumed to be active in generating a given document, and a terminal node that represents a given word in the given document; wherein the given word is not associated with the concept represented by the cluster node.
| 0.5 |
9,715,509 | 6 | 7 |
6. An electronic device comprising: a display screen configured to display a navigation menu comprising document identifiers, each document being associated with a plurality of numerical values of descriptive data characterizing it, a receiver having a central processing unit configured to: calculate, in a multi-dimensional space, coordinates of identifiers associated with identified documents, from numerical values of low-level descriptive data determined from an audio component of the identified documents, said multi-dimensional space comprising as many dimensions as the number of low-level descriptive data of the identified documents; divide the navigation menu into a set number of regions grouping document identifiers, the display screen being able to display an outer contour of each determined region; and position, on the screen, the identifier of each identified document based on its calculated coordinates; an interface configured to receive a command for selection of a region among the set number of regions, said command for selection triggering the display of a modified navigation menu having the same set number of regions and which only contains identifiers of the selected region.
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6. An electronic device comprising: a display screen configured to display a navigation menu comprising document identifiers, each document being associated with a plurality of numerical values of descriptive data characterizing it, a receiver having a central processing unit configured to: calculate, in a multi-dimensional space, coordinates of identifiers associated with identified documents, from numerical values of low-level descriptive data determined from an audio component of the identified documents, said multi-dimensional space comprising as many dimensions as the number of low-level descriptive data of the identified documents; divide the navigation menu into a set number of regions grouping document identifiers, the display screen being able to display an outer contour of each determined region; and position, on the screen, the identifier of each identified document based on its calculated coordinates; an interface configured to receive a command for selection of a region among the set number of regions, said command for selection triggering the display of a modified navigation menu having the same set number of regions and which only contains identifiers of the selected region. 7. The electronic device of claim 6 , wherein the numerical values taken into account for determining the position of the identifiers within the navigation menu are different than those used for dividing into regions.
| 0.629693 |
9,424,294 | 1 | 3 |
1. A method comprising: receiving one or more first search queries; processing fields in the one or more first search queries wherein the processing comprises at least one of address standardization, proximity boundaries, nickname interpretation, extraction of at least prefix, and generation of at least one non-literal key; constructing one or more second search queries associated with the one or more first search queries wherein the one or more second search queries are stack-based; sending the one or more second search queries to one or more search conductors wherein the one or more search conductors are associated with collections specified in the one or more second search queries; scoring a match of one or more fields of one or more records against the one or more second search queries; adding the one or more records to a results list based on the scoring; continually scoring the one or more records until all records in a partition have been processed; sorting the results list; receiving and collating the results list; performing aggregate analytics processing on the results list wherein the aggregate analytics processing comprises extracting, disambiguating, normalizing, grouping, and indexing a first set of facets from documents wherein the facets comprise different levels of specificity; returning results of the aggregate analytics processing; storing the results in a knowledge base wherein the knowledge base is part of an in-memory database system architecture; loading new documents into an in-memory database; extracting a second set of disambiguated facets from the new documents; and comparing the second set of disambiguated facets with the first set of disambiguated facets wherein the comparing comprises: updating the knowledge base and returning the ID of matching facets; and assigning a unique ID to unmatched facets, associating the unmatched facets with a cluster of defining features, and storing the unmatched facets and the cluster in the knowledge base.
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1. A method comprising: receiving one or more first search queries; processing fields in the one or more first search queries wherein the processing comprises at least one of address standardization, proximity boundaries, nickname interpretation, extraction of at least prefix, and generation of at least one non-literal key; constructing one or more second search queries associated with the one or more first search queries wherein the one or more second search queries are stack-based; sending the one or more second search queries to one or more search conductors wherein the one or more search conductors are associated with collections specified in the one or more second search queries; scoring a match of one or more fields of one or more records against the one or more second search queries; adding the one or more records to a results list based on the scoring; continually scoring the one or more records until all records in a partition have been processed; sorting the results list; receiving and collating the results list; performing aggregate analytics processing on the results list wherein the aggregate analytics processing comprises extracting, disambiguating, normalizing, grouping, and indexing a first set of facets from documents wherein the facets comprise different levels of specificity; returning results of the aggregate analytics processing; storing the results in a knowledge base wherein the knowledge base is part of an in-memory database system architecture; loading new documents into an in-memory database; extracting a second set of disambiguated facets from the new documents; and comparing the second set of disambiguated facets with the first set of disambiguated facets wherein the comparing comprises: updating the knowledge base and returning the ID of matching facets; and assigning a unique ID to unmatched facets, associating the unmatched facets with a cluster of defining features, and storing the unmatched facets and the cluster in the knowledge base. 3. The method according to claim 1 , wherein the one or more first search queries are represented in a compact format or a binary format.
| 0.641361 |
8,655,650 | 10 | 11 |
10. The method of claim 9 further comprises receiving two or more data streams having voice data encoded therein at a receiver, where each data stream corresponds to a channel in the system, and decoding each data stream into a set of speech coding parameters.
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10. The method of claim 9 further comprises receiving two or more data streams having voice data encoded therein at a receiver, where each data stream corresponds to a channel in the system, and decoding each data stream into a set of speech coding parameters. 11. The method of claim 10 wherein the voice data encoded in the data streams is encoded in accordance with mixed excitation linear prediction (MELP), such that speech coding parameters include gain, pitch, unvoiced flag, jitter, bandpass voicing and a line spectral frequency (LSF) vector.
| 0.5 |
9,069,754 | 7 | 14 |
7. A method comprising: determining text subgroups within an electronic text; determining a relevance score for each word of one or more words within the determined text subgroups, the relevance score based on one of a frequency of occurrence of the word within one of the determined text subgroups and a type of the word within one of the determined text subgroups; selecting, by an electronic device, a text subgroup from the determined text subgroups that corresponds to a current user position within the electronic text; selecting, by the electronic device, a text seed within the selected text subgroup based on the relevance scores of the words within the selected text subgroup; determining a first similarity relationship between the selected text seed and one or more of the determined text subgroups adjacent to the selected text subgroup that do not include the selected text seed; creating a text cluster by associating the text seed with the one or more adjacent determined text subgroups based on the first similarity relationship; and for each of the determined text subgroups outside of the text cluster: determining an activity indication of time when a user has read the determined text subgroup; determining a second similarity relationship between content of the determined text subgroup and the text cluster; and linking the determined text subgroup to the text cluster based on the second similarity relationship and on the determined time the user read the text subgroup.
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7. A method comprising: determining text subgroups within an electronic text; determining a relevance score for each word of one or more words within the determined text subgroups, the relevance score based on one of a frequency of occurrence of the word within one of the determined text subgroups and a type of the word within one of the determined text subgroups; selecting, by an electronic device, a text subgroup from the determined text subgroups that corresponds to a current user position within the electronic text; selecting, by the electronic device, a text seed within the selected text subgroup based on the relevance scores of the words within the selected text subgroup; determining a first similarity relationship between the selected text seed and one or more of the determined text subgroups adjacent to the selected text subgroup that do not include the selected text seed; creating a text cluster by associating the text seed with the one or more adjacent determined text subgroups based on the first similarity relationship; and for each of the determined text subgroups outside of the text cluster: determining an activity indication of time when a user has read the determined text subgroup; determining a second similarity relationship between content of the determined text subgroup and the text cluster; and linking the determined text subgroup to the text cluster based on the second similarity relationship and on the determined time the user read the text subgroup. 14. The method of claim 7 , wherein determining the second similarity relationship comprises: using a semantic graph representing relations between words to compare words of the text cluster and words in the determined text subgroup; and using the comparison to link the determined text subgroup with the text cluster.
| 0.597468 |
9,082,310 | 17 | 23 |
17. The method of claim 1 , further comprising: (e) automatically generating a first answer to the first question instance based on the first region definition in the first question instance and the data set.
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17. The method of claim 1 , further comprising: (e) automatically generating a first answer to the first question instance based on the first region definition in the first question instance and the data set. 23. The method of claim 17 , further comprising: (f) receiving input from the user representing feedback on the first answer; and (g) storing, in a computer-readable medium, a record of the input.
| 0.786026 |
9,280,535 | 21 | 22 |
21. The computer-readable storage media of claim 20 , the method further comprising executing the database query on an inverted index of a database.
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21. The computer-readable storage media of claim 20 , the method further comprising executing the database query on an inverted index of a database. 22. The computer-readable storage media of claim 21 , wherein the inverted index is based on one or more materialized views of the database.
| 0.5 |
9,934,130 | 9 | 13 |
9. A method for performing integration testing using an unstructured database, the method comprising: determining a driver class file for an integration testing tool to connect to a specified unstructured database of a plurality of unstructured databases, where the driver class file includes parameters of the specified unstructured database, the parameters are validated to connect the integration testing tool to the specified unstructured database, the driver class file is determined from a plurality of files associated with the plurality of unstructured databases the integration testing tool is to test at least one function performed by an application, the application is to store data in the specified unstructured database responsive to performing the at least one function, and the determining is performed by a computer; generating a connectivity driver for the specified unstructured database by determining a path to a location of a folder of the driver class file, and using the path to the location of the folder of the driver class file to generate the connectivity driver for the specified unstructured database, where the path is used to access the driver class file, and the generating is performed by the computer; determining dependency files for the specified unstructured database, where the dependency files are used to retrieve the data from the specified unstructured database, the dependency files are used to update the data in the specified unstructured database, the dependency files are determined from the plurality of files associated with the plurality of unstructured databases, and the determining of the dependency files is performed by the computer; storing the driver class file, the connectivity driver, and the dependency files in a library of the integration testing tool, where the library of the integration testing tool stores executable files for integration testing of the application, and the adding is performed by the computer; establishing a connection between the integration testing tool and the specified unstructured database, where the connection is established using the driver class file and the connectivity driver, and the establishing is performed by the computer; generating a query to access the data in the specified unstructured database, where the query is in a format compatible with the specified unstructured database, the data represents a result based on performing the at least one function, and the generating of the query is performed by the computer; sending the query to the specified unstructured database for execution, where the dependency files are used, based on the query, to retrieve query results from the specified unstructured database, and the sending is performed by the computer; receiving the query results based on performing the at least one function when the query is executed, where the receiving is performed by the computer; comparing the query results to validation data, where the comparing is performed by the computer; determining whether the at least one function operates in a determined manner based on the comparing, where the determining is performed by the computer; and validating the query results based on comparing the query results to the validation data to determine whether the at least one function operates in the determined manner, where the validating is performed by the computer.
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9. A method for performing integration testing using an unstructured database, the method comprising: determining a driver class file for an integration testing tool to connect to a specified unstructured database of a plurality of unstructured databases, where the driver class file includes parameters of the specified unstructured database, the parameters are validated to connect the integration testing tool to the specified unstructured database, the driver class file is determined from a plurality of files associated with the plurality of unstructured databases the integration testing tool is to test at least one function performed by an application, the application is to store data in the specified unstructured database responsive to performing the at least one function, and the determining is performed by a computer; generating a connectivity driver for the specified unstructured database by determining a path to a location of a folder of the driver class file, and using the path to the location of the folder of the driver class file to generate the connectivity driver for the specified unstructured database, where the path is used to access the driver class file, and the generating is performed by the computer; determining dependency files for the specified unstructured database, where the dependency files are used to retrieve the data from the specified unstructured database, the dependency files are used to update the data in the specified unstructured database, the dependency files are determined from the plurality of files associated with the plurality of unstructured databases, and the determining of the dependency files is performed by the computer; storing the driver class file, the connectivity driver, and the dependency files in a library of the integration testing tool, where the library of the integration testing tool stores executable files for integration testing of the application, and the adding is performed by the computer; establishing a connection between the integration testing tool and the specified unstructured database, where the connection is established using the driver class file and the connectivity driver, and the establishing is performed by the computer; generating a query to access the data in the specified unstructured database, where the query is in a format compatible with the specified unstructured database, the data represents a result based on performing the at least one function, and the generating of the query is performed by the computer; sending the query to the specified unstructured database for execution, where the dependency files are used, based on the query, to retrieve query results from the specified unstructured database, and the sending is performed by the computer; receiving the query results based on performing the at least one function when the query is executed, where the receiving is performed by the computer; comparing the query results to validation data, where the comparing is performed by the computer; determining whether the at least one function operates in a determined manner based on the comparing, where the determining is performed by the computer; and validating the query results based on comparing the query results to the validation data to determine whether the at least one function operates in the determined manner, where the validating is performed by the computer. 13. The method of claim 9 , further comprising: testing the connection between the integration testing tool and the specified unstructured database prior to establishing the connection between the integration testing tool and the specified unstructured database, where the testing is performed by the computer; in response to determining that the connection between the integration testing tool and the specified unstructured database is unsuccessful and the driver class file is correctly determined, or the connection between the integration testing tool and the specified unstructured database is unsuccessful and the driver class file is incorrectly determined, determining a dependency file or a different driver class file, respectively, to store in the library, where the dependency file or the different driver class file, respectively, is determined from the plurality of files associated with the plurality of unstructured databases, the dependency file or the different driver class file, respectively, is determined to address an error related to dependencies or an error related to validation of the parameters of the specified unstructured database, and the determining of the dependency file or the different driver class file is performed by the computer, and storing the dependency file or the different driver class file, respectively, to the library, where the storing of the dependency file or the different driver class file is performed by the computer; and re-testing the connection between the integration testing tool and the specified unstructured database to establish the connection between the integration testing tool and the specified unstructured database, or iteratively storing another dependency file or another driver class file, respectively, in the library until successful establishment of the connection between the integration testing tool and the specified unstructured database, where the re-testing is performed by the computer.
| 0.5 |
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