patent_num
int64 3.93M
10.2M
| claim_num1
int64 1
519
| claim_num2
int64 2
520
| sentence1
stringlengths 40
15.9k
| sentence2
stringlengths 88
20k
| label
float64 0.5
1
|
|---|---|---|---|---|---|
9,135,242 | 1 | 8 | 1. A computerized method for the analysis of textual data, comprising: receiving, from one or more memories at one or more processors, textual data to be analyzed; using the one or more processors, formatting the textual data for subsequent analysis; using the one or more processors, applying a probabilistic topic model to the textual data to extract a set of semantically meaningful topics that collectively describe all or a portion of the textual data; using a keyword weighting module executed on the one or more processors, generating a topic cloud view representing the topics as a tagcloud with each being associated with a plurality of keywords; using a topic ordering module executed on the one or more processors, generating a document distribution view representing a distribution of all or a portion of the textual data across multiple topics; using a document entropy calculation module executed on the one or more processors, generating a document scatterplot view representing how many topics are attributable to all or a portion of the textual data; using a temporal topic trend calculation module executed on the one or more processors, generating a temporal view representing changes in the occurrence of topics over time in relation to all or a portion of the textual data; and displaying one or more of the topic cloud view, the document distribution view, the document scatterplot view, and the temporal view to a user in the analysis of all or a portion of the textual data. | 1. A computerized method for the analysis of textual data, comprising: receiving, from one or more memories at one or more processors, textual data to be analyzed; using the one or more processors, formatting the textual data for subsequent analysis; using the one or more processors, applying a probabilistic topic model to the textual data to extract a set of semantically meaningful topics that collectively describe all or a portion of the textual data; using a keyword weighting module executed on the one or more processors, generating a topic cloud view representing the topics as a tagcloud with each being associated with a plurality of keywords; using a topic ordering module executed on the one or more processors, generating a document distribution view representing a distribution of all or a portion of the textual data across multiple topics; using a document entropy calculation module executed on the one or more processors, generating a document scatterplot view representing how many topics are attributable to all or a portion of the textual data; using a temporal topic trend calculation module executed on the one or more processors, generating a temporal view representing changes in the occurrence of topics over time in relation to all or a portion of the textual data; and displaying one or more of the topic cloud view, the document distribution view, the document scatterplot view, and the temporal view to a user in the analysis of all or a portion of the textual data. 8. The computerized method of claim 1 , wherein the keywords are highlighted to indicate their importance to multiple topics. | 0.897373 |
7,543,225 | 7 | 14 | 7. A method for dynamic configuration of a gaming display, said method comprising: processing a markup language file for use in a gaming application to identify tokens to be resolved to format an interface displayed to a player for a gaming application, said markup language file including static information and variable information defined by one or more tokens relating to at least one of game theme, game display and player identity; resolving said tokens based on token resolution information found external to said markup language file to generate a resolved markup language file without modifying read only, regulatory approved game instructions for execution of a gaming application in conjunction with said interface provided by said resolved markup language file; displaying said interface provided by said resolved markup language at a gaming device having a display to facilitate play of said gaming application; and dynamically adjusting said interface for said gaming application based on token values updated based on a change in at least one of a user, a game, and a game condition. | 7. A method for dynamic configuration of a gaming display, said method comprising: processing a markup language file for use in a gaming application to identify tokens to be resolved to format an interface displayed to a player for a gaming application, said markup language file including static information and variable information defined by one or more tokens relating to at least one of game theme, game display and player identity; resolving said tokens based on token resolution information found external to said markup language file to generate a resolved markup language file without modifying read only, regulatory approved game instructions for execution of a gaming application in conjunction with said interface provided by said resolved markup language file; displaying said interface provided by said resolved markup language at a gaming device having a display to facilitate play of said gaming application; and dynamically adjusting said interface for said gaming application based on token values updated based on a change in at least one of a user, a game, and a game condition. 14. The method of claim 7 , wherein an external process affects selection of said markup language file for processing and display. | 0.927617 |
5,546,575 | 69 | 73 | 69. A method of accessing a database comprising the following steps: specifying a compacted data record to be retrieved from a database; retrieving the compacted data record from within a partition and a subpartition of the database; determining a partition number associated with the partition and a subpartition number associated with the subpartition; specifying a field of the compacted data record; reading a compacted data value from the field; determining a field number associated with the field; locating a pack method in a record information table, the pack method dependent upon the partition number, the subpartition number and the field number; and creating a data value from the pack method and the compacted data value, the data value associated with the specified compacted data record. | 69. A method of accessing a database comprising the following steps: specifying a compacted data record to be retrieved from a database; retrieving the compacted data record from within a partition and a subpartition of the database; determining a partition number associated with the partition and a subpartition number associated with the subpartition; specifying a field of the compacted data record; reading a compacted data value from the field; determining a field number associated with the field; locating a pack method in a record information table, the pack method dependent upon the partition number, the subpartition number and the field number; and creating a data value from the pack method and the compacted data value, the data value associated with the specified compacted data record. 73. A database access method according to claim 69 wherein the pack method specifies a storage number; and the creating step comprises the following steps: locating a status value in a text table, the status value equated to the field number and indicating that the associated field is text; locating a code in a storage definition table, the code equated to the storage number; calculating a numeric equivalent associated with the compacted data value and the code; and locating a data value in a text translation table, the data value equated to the numeric equivalent. | 0.858101 |
9,620,128 | 36 | 37 | 36. The computationally-implemented method of claim 33 , wherein said storing a reference to a location of adaptation data, wherein the adaptation data is at least partly based on at least one speech interaction of a particular party comprises: storing the reference to the location of adaptation data, wherein the adaptation data includes data linking pronunciation of one or more phonemes to one or more concepts. | 36. The computationally-implemented method of claim 33 , wherein said storing a reference to a location of adaptation data, wherein the adaptation data is at least partly based on at least one speech interaction of a particular party comprises: storing the reference to the location of adaptation data, wherein the adaptation data includes data linking pronunciation of one or more phonemes to one or more concepts. 37. The computationally-implemented method of claim 36 , wherein said storing the reference to the location of adaptation data, wherein the adaptation data includes data linking pronunciation of one or more phonemes to one or more concepts comprises: storing the reference to the location of adaptation data, wherein the adaptation data includes data linking pronunciation of phonemes of the word MONEY to an interaction with an automated teller machine device. | 0.931946 |
9,852,379 | 33 | 34 | 33. A computer-implemented method of scoring a text based on at least predicted figurative word usage in the constructed texts, the method comprising: accessing a text to be evaluated with a processing system; identifying content words in the text with the processing system; extracting one or more features from each of the content words with the processing system, wherein extracting one or more features includes determining whether a particular content word belongs in a particular word group, wherein the particular word group is associated with a figurative usage likelihood; predicting, with a processing system, whether each of the content words is being used figuratively in the text, the predicting being based on a prediction model and the extracted one or more features; and generating an evaluation score with the processing system for the text based on the predictions. | 33. A computer-implemented method of scoring a text based on at least predicted figurative word usage in the constructed texts, the method comprising: accessing a text to be evaluated with a processing system; identifying content words in the text with the processing system; extracting one or more features from each of the content words with the processing system, wherein extracting one or more features includes determining whether a particular content word belongs in a particular word group, wherein the particular word group is associated with a figurative usage likelihood; predicting, with a processing system, whether each of the content words is being used figuratively in the text, the predicting being based on a prediction model and the extracted one or more features; and generating an evaluation score with the processing system for the text based on the predictions. 34. The method of claim 33 , wherein extracting one or more features further comprises: identifying an associate word that is associated with the particular content word; determining whether the associate word belongs in a particular associate word group, wherein the particular associate word group is associated with another figurative usage likelihood; wherein a prediction of whether the particular content word is being used figuratively is based on the figurative usage likelihood and the another figurative usage likelihood. | 0.877254 |
4,877,408 | 5 | 6 | 5. The competitive computer educational game recited in claim 2, 3, or 4 further incorporating: a voice synthesizer to verbally ask the questions. | 5. The competitive computer educational game recited in claim 2, 3, or 4 further incorporating: a voice synthesizer to verbally ask the questions. 6. The competitive computer educational game as set forth in claim 5 further incorporating a means for recording each students score and handicap for further evaluation by the teacher. | 0.897778 |
8,856,180 | 17 | 18 | 17. The method according to claim 12 , wherein the primary file is a HTML/JS file. | 17. The method according to claim 12 , wherein the primary file is a HTML/JS file. 18. The method according to claim 17 , wherein the HTML/JS file renders individual pages of the electronic publication when executed by the device. | 0.960569 |
8,725,517 | 1 | 2 | 1. A method comprising: selecting a recursive transition network flow controller from a database, to yield a selected top level flow controller; selecting an available reusable subdialog for an application part below the selected top level flow controller; developing, via a processor, a subdialog for each application part not associated with the available reusable subdialog, to yield developed subdialogs; and deploying a spoken dialog service using the selected top level flow controller, the available reusable subdialog, and the developed subdialogs. | 1. A method comprising: selecting a recursive transition network flow controller from a database, to yield a selected top level flow controller; selecting an available reusable subdialog for an application part below the selected top level flow controller; developing, via a processor, a subdialog for each application part not associated with the available reusable subdialog, to yield developed subdialogs; and deploying a spoken dialog service using the selected top level flow controller, the available reusable subdialog, and the developed subdialogs. 2. The method of claim 1 , wherein the available reusable subdialog is isolated from application dependencies. | 0.856771 |
9,914,213 | 1 | 10 | 1. A method implemented by one or more processors, comprising: generating a candidate end effector motion vector defining motion to move a grasping end effector of a robot from a current pose to an additional pose; identifying a current image captured by a vision sensor associated with the robot, the current image capturing the grasping end effector and at least one object in an environment of the robot; applying the current image and the candidate end effector motion vector as input to a trained grasp convolutional neural network; generating, over the trained grasp convolutional neural network, a measure of successful grasp of the object with application of the motion, the measure being generated based on the application of the image and the end effector motion vector to the trained grasp convolutional neural network; identifying a desired object semantic feature; applying, as input to a semantic convolutional neural network, a spatial transformation of the current image or of an additional image captured by the vision sensor; generating, over the semantic convolutional neural network based on the spatial transformation, an additional measure that indicates whether the desired object semantic feature is present in the spatial transformation; generating an end effector command based on the measure of successful grasp and the additional measure that indicates whether the desired object semantic feature is present; and providing the end effector command to one or more actuators of the robot. | 1. A method implemented by one or more processors, comprising: generating a candidate end effector motion vector defining motion to move a grasping end effector of a robot from a current pose to an additional pose; identifying a current image captured by a vision sensor associated with the robot, the current image capturing the grasping end effector and at least one object in an environment of the robot; applying the current image and the candidate end effector motion vector as input to a trained grasp convolutional neural network; generating, over the trained grasp convolutional neural network, a measure of successful grasp of the object with application of the motion, the measure being generated based on the application of the image and the end effector motion vector to the trained grasp convolutional neural network; identifying a desired object semantic feature; applying, as input to a semantic convolutional neural network, a spatial transformation of the current image or of an additional image captured by the vision sensor; generating, over the semantic convolutional neural network based on the spatial transformation, an additional measure that indicates whether the desired object semantic feature is present in the spatial transformation; generating an end effector command based on the measure of successful grasp and the additional measure that indicates whether the desired object semantic feature is present; and providing the end effector command to one or more actuators of the robot. 10. The method of claim 1 , wherein the end effector command is an end effector motion command and wherein generating the end effector motion command comprises generating the end effector motion command to conform to the candidate end effector motion vector. | 0.930458 |
8,108,386 | 1 | 4 | 1. A method of searching and retrieving from a database, comprising the steps of: establishing a communication link between a requestor and a service provider, and the communication link originating from the requestor; receiving requested database record information from the requestor, requestor inputting a search query that includes non-sequential first and last elements of a plurality of different terms in a single search field of a requested database record, wherein first and last elements are each a single alphanumeric character, and the search query omits a plurality of elements of the search field positioned between the first and last elements; and executing the search query; selecting at least one database record that matches the search query and supplying the requestor with information from the selected database record. | 1. A method of searching and retrieving from a database, comprising the steps of: establishing a communication link between a requestor and a service provider, and the communication link originating from the requestor; receiving requested database record information from the requestor, requestor inputting a search query that includes non-sequential first and last elements of a plurality of different terms in a single search field of a requested database record, wherein first and last elements are each a single alphanumeric character, and the search query omits a plurality of elements of the search field positioned between the first and last elements; and executing the search query; selecting at least one database record that matches the search query and supplying the requestor with information from the selected database record. 4. The method of claim 1 wherein the search query includes at least one additional element that is other than non-sequential first and last elements of a term of a search field. | 0.856331 |
8,566,029 | 1 | 8 | 1. A computer-implemented method comprising: generating, at one or more processors, a first search engine results page which includes links to one or more points-of-interest that satisfy a query; receiving, at the one or more processors, one or more signals indicating that a link to a point-of-interest was selected by a user; responsive to receiving the one or more signals: selecting, at the one or more processors, a plurality of geographic areas, each geographic area being associated with a set of information, each set of information comprising one or more identifiers of points-of-interest and a score associated with each identifier, determining, at the one or more processors, for each of the selected geographic areas, an increment value, determining, at the one or more processors, for each of the selected geographic areas, a score associated with the selected point-of-interest, incrementing, at the one or more processors, for each of the selected geographic areas, the score by the increment value, and storing, by the one or more processors, for each of the selected geographic areas, the incremented score in the set of information associated with the respective geographic area, the incremented score being stored in association with an identifier of the selected point-of-interest; and using, at the one or more processors, the incremented scores stored in the sets of information associated with the selected geographic areas to generate a second search engine results page. | 1. A computer-implemented method comprising: generating, at one or more processors, a first search engine results page which includes links to one or more points-of-interest that satisfy a query; receiving, at the one or more processors, one or more signals indicating that a link to a point-of-interest was selected by a user; responsive to receiving the one or more signals: selecting, at the one or more processors, a plurality of geographic areas, each geographic area being associated with a set of information, each set of information comprising one or more identifiers of points-of-interest and a score associated with each identifier, determining, at the one or more processors, for each of the selected geographic areas, an increment value, determining, at the one or more processors, for each of the selected geographic areas, a score associated with the selected point-of-interest, incrementing, at the one or more processors, for each of the selected geographic areas, the score by the increment value, and storing, by the one or more processors, for each of the selected geographic areas, the incremented score in the set of information associated with the respective geographic area, the incremented score being stored in association with an identifier of the selected point-of-interest; and using, at the one or more processors, the incremented scores stored in the sets of information associated with the selected geographic areas to generate a second search engine results page. 8. The method of claim 1 , wherein: the signal further indicates a duration between an initial click on the link by the user, and a subsequent click by the user; and determining the increment value comprises selecting, as the increment value, a value which is proportional to the duration. | 0.832172 |
8,359,279 | 9 | 17 | 9. A system comprising a processing unit, one or more input devices, and a display, the processing unit being configured to implement a graphical user interface by processing user input provided via the input device(s) and by rendering images to the display, the graphical user interface enabling a user to associate each of a plurality of data items with any one of a plurality of clusters in a system-assisted manner and comprising: a visual representation of each of the data items; a visual representation of each of the clusters; means for enabling the user to selectively associate each data item representation with any one of the cluster representations; and means for outputting a user-perceivable indication that a particular data item representation should be associated with a particular cluster representation based on a system-generated recommendation. | 9. A system comprising a processing unit, one or more input devices, and a display, the processing unit being configured to implement a graphical user interface by processing user input provided via the input device(s) and by rendering images to the display, the graphical user interface enabling a user to associate each of a plurality of data items with any one of a plurality of clusters in a system-assisted manner and comprising: a visual representation of each of the data items; a visual representation of each of the clusters; means for enabling the user to selectively associate each data item representation with any one of the cluster representations; and means for outputting a user-perceivable indication that a particular data item representation should be associated with a particular cluster representation based on a system-generated recommendation. 17. The system of claim 9 , wherein the data items contain textual elements and wherein the graphical user interface further comprises: a means for inputting a text query to be executed against each of the data items; and a means for visually identifying one or more of the data items representations that correspond to data items that are determined to match the text query. | 0.595905 |
8,234,174 | 12 | 13 | 12. The method of claim 9 , further comprising: a. providing at least one remote employee user designated by the remote company user; and b. configuring the host server to manage remote company user and employee user access to the company user webpages. | 12. The method of claim 9 , further comprising: a. providing at least one remote employee user designated by the remote company user; and b. configuring the host server to manage remote company user and employee user access to the company user webpages. 13. The method of claim 12 , wherein a. different employee users are provided different levels of access to the inventory listing information. | 0.920847 |
8,712,761 | 2 | 3 | 2. A computer-implemented method comprising: receiving, at a computing device having one or more processors, a message template to be translated from a source language to a target language, the message template including a text portion and one or more template placeholders, whereby the message template is used to generate a customized output message by replacing the one or more template placeholders with customized content; parsing, at the computing device, the message template to identify the text portion and the one or more template placeholders; generating, at the computing device, one or more non-editable objects, each of the one or more non-editable objects corresponding to one of the one or more template placeholders; generating, at the computing device, a display message template by replacing each of the one or more template placeholders with its corresponding non-editable object in the message template, the display message template including the text portion to be translated; providing, from the computing device, the display message template to a user device; receiving, at the computing device, a translated display message template from the user device, the translated message including a translated text portion and the one or more non-editable objects, the translated text portion being in the target language and corresponding to the text portion of the message template; and generating, at the computing device, a translated message template based on the translated display message template, the translated message template including the translated text portion and the one or more template placeholders. | 2. A computer-implemented method comprising: receiving, at a computing device having one or more processors, a message template to be translated from a source language to a target language, the message template including a text portion and one or more template placeholders, whereby the message template is used to generate a customized output message by replacing the one or more template placeholders with customized content; parsing, at the computing device, the message template to identify the text portion and the one or more template placeholders; generating, at the computing device, one or more non-editable objects, each of the one or more non-editable objects corresponding to one of the one or more template placeholders; generating, at the computing device, a display message template by replacing each of the one or more template placeholders with its corresponding non-editable object in the message template, the display message template including the text portion to be translated; providing, from the computing device, the display message template to a user device; receiving, at the computing device, a translated display message template from the user device, the translated message including a translated text portion and the one or more non-editable objects, the translated text portion being in the target language and corresponding to the text portion of the message template; and generating, at the computing device, a translated message template based on the translated display message template, the translated message template including the translated text portion and the one or more template placeholders. 3. The method of claim 2 , further comprising providing, for display at the user device, an environment that includes a first portion that displays the display message template, including the one or more template placeholders, and a second portion that receives text input from the user, wherein the user enters the translated text portion at the second portion. | 0.642292 |
9,489,577 | 18 | 19 | 18. The apparatus of claim 17 wherein the visual similarity process further comprises comparing videos to determine whether the videos contain speech. | 18. The apparatus of claim 17 wherein the visual similarity process further comprises comparing videos to determine whether the videos contain speech. 19. The apparatus of claim 18 wherein comparing videos comprises pixel comparison. | 0.950602 |
9,129,216 | 1 | 2 | 1. A computer implemented method, using a processor of a server, for recommending images, the method comprising: receiving content comprising text, processing the content to extract data comprising text features, wherein the text features form a text feature vector; receiving a candidate set of image suggestions, the candidate set comprising images that may be submitted to a user taken from one or more collections of images, and for each image in the candidate set of image suggestions, processing the image to extract data comprising image features, wherein the image features form an image feature vector, receiving user information and processing the information to extract data comprising user features, wherein the user features form a user feature vector; storing the text feature vector, image feature vector, and user feature vector as a triplet in a reference database; and applying means for machine learning using said triplets to learn an association function to calculate an Illustration Index, comprising a score that measures the level of association of the image suggestion to the content; using the triplets stored in the reference database to generate one or more suggested images to be used with one or a plurality of subsequent text content input by a user in a user device; and displaying the one or more suggested images on a user device. | 1. A computer implemented method, using a processor of a server, for recommending images, the method comprising: receiving content comprising text, processing the content to extract data comprising text features, wherein the text features form a text feature vector; receiving a candidate set of image suggestions, the candidate set comprising images that may be submitted to a user taken from one or more collections of images, and for each image in the candidate set of image suggestions, processing the image to extract data comprising image features, wherein the image features form an image feature vector, receiving user information and processing the information to extract data comprising user features, wherein the user features form a user feature vector; storing the text feature vector, image feature vector, and user feature vector as a triplet in a reference database; and applying means for machine learning using said triplets to learn an association function to calculate an Illustration Index, comprising a score that measures the level of association of the image suggestion to the content; using the triplets stored in the reference database to generate one or more suggested images to be used with one or a plurality of subsequent text content input by a user in a user device; and displaying the one or more suggested images on a user device. 2. The method as in claim 1 , wherein the one or more collections of images are images stored on the user device. | 0.896709 |
9,336,290 | 7 | 8 | 7. The system of claim 6 , comprising providing a user interface to a client, the user interface configured to present at least one question as to whether an extracted value of the one or more values paired with its corresponding attribute accurately characterizes the document, wherein at least one extracted value paired with its corresponding attribute is a candidate ontology term not found in the ontology and is presented in the at least one question. | 7. The system of claim 6 , comprising providing a user interface to a client, the user interface configured to present at least one question as to whether an extracted value of the one or more values paired with its corresponding attribute accurately characterizes the document, wherein at least one extracted value paired with its corresponding attribute is a candidate ontology term not found in the ontology and is presented in the at least one question. 8. The system of claim 7 , comprising receiving a response to the at least one question from the client though the user interface indicating that the attribute-value pair accurately characterizes the data object. | 0.897485 |
8,521,748 | 1 | 6 | 1. A method of managing metadata in a relational database system using a processor, the metadata created in a form of rough values corresponding to collections of values, wherein each rough value represents summarized information about values, wherein the values are elements of the corresponding collection of values, and wherein each rough value being substantially smaller than the corresponding collection of values, the method comprising: assigning a collection of values to a structure dictionary, wherein each of the values represents the value of a row for an attribute and has a unique ordinal number within the collection, and wherein the structure dictionary contains structures defined based on at least one of interaction with a user of the system via an interface, automatic detection of structures occurring in data, and predetermined information about structures relevant to data content that is stored in the system; forming a match granule containing summarized information about the assignment of the ordinal numbers of the elements in the collection of values to the structures in the structure dictionary; for each structure in the structure dictionary, forming a structure granule containing summarized information about one or more elements in the collection of values for which an ordinal number was assigned to the structure; and gathering summarized information represented by the match granule and one or more structure granules to form a rough value. | 1. A method of managing metadata in a relational database system using a processor, the metadata created in a form of rough values corresponding to collections of values, wherein each rough value represents summarized information about values, wherein the values are elements of the corresponding collection of values, and wherein each rough value being substantially smaller than the corresponding collection of values, the method comprising: assigning a collection of values to a structure dictionary, wherein each of the values represents the value of a row for an attribute and has a unique ordinal number within the collection, and wherein the structure dictionary contains structures defined based on at least one of interaction with a user of the system via an interface, automatic detection of structures occurring in data, and predetermined information about structures relevant to data content that is stored in the system; forming a match granule containing summarized information about the assignment of the ordinal numbers of the elements in the collection of values to the structures in the structure dictionary; for each structure in the structure dictionary, forming a structure granule containing summarized information about one or more elements in the collection of values for which an ordinal number was assigned to the structure; and gathering summarized information represented by the match granule and one or more structure granules to form a rough value. 6. The method according to claim 1 , further comprising at least one of adding structures into and modifying the structures in the structure dictionary, and at least one of: immediately re-forming the rough values to reflect the at least one of the addition and modification; applying the at least one addition and modification to rough values corresponding to collections of values with new values inserted, or old values deleted or updated after said modification occurred, but not to already existing rough values; evaluating whether said addition or modification should be applied to re-form the already existing rough values based on a group of criteria including at least one of minimizing the cost of forming the structure granules corresponding to the added or modified structures and maximizing the estimated efficiency of using rough values while resolving queries, wherein the rough values are accessible independently from their corresponding collections of values, and the rough values are applied to minimize the amount of accesses to said corresponding collections of values while resolving queries; and providing an interface to a user of the system, said interface reporting the cost of forming the structure granules corresponding to the added or modified structures and the estimated efficiency of using rough values while resolving queries, wherein the rough values are accessible independently from their corresponding collections of values, said rough values are applied to minimize the amount of accesses to said corresponding collections of values while resolving queries, and said user is able to decide whether the modified structure dictionary should be applied to re-form rough values. | 0.595609 |
8,269,722 | 1 | 5 | 1. A gesture recognition system, comprising: an image pick-up device, for capturing an image data containing a hand image; a template database, for recording multiple gesture templates representing different gestures, wherein the gesture templates are classified by angles and are respectively stored in gesture template libraries of different angle classes; a processor, for communicating with the image pick-up device and obtaining the image data, finding out a skin part from the image data, producing a skin edge by using an edge detection means, and then classifying the skin edge into multiple edge parts of different angle classes according to angles of the skin edge; an operation engine, having multiple parallel operation units respectively for performing template matching at different angles, wherein the edge parts of different angle classes are respectively sent to different parallel operation units for template matching, so as to find out the gesture templates most resembling the edge parts in the corresponding gesture template libraries of different angle classes; an optimal template selection means, for further selecting an optimal gesture template from the resembling gesture templates found out by the parallel operation units; and a display terminal, for displaying a gesture image represented by the optimal gesture template. | 1. A gesture recognition system, comprising: an image pick-up device, for capturing an image data containing a hand image; a template database, for recording multiple gesture templates representing different gestures, wherein the gesture templates are classified by angles and are respectively stored in gesture template libraries of different angle classes; a processor, for communicating with the image pick-up device and obtaining the image data, finding out a skin part from the image data, producing a skin edge by using an edge detection means, and then classifying the skin edge into multiple edge parts of different angle classes according to angles of the skin edge; an operation engine, having multiple parallel operation units respectively for performing template matching at different angles, wherein the edge parts of different angle classes are respectively sent to different parallel operation units for template matching, so as to find out the gesture templates most resembling the edge parts in the corresponding gesture template libraries of different angle classes; an optimal template selection means, for further selecting an optimal gesture template from the resembling gesture templates found out by the parallel operation units; and a display terminal, for displaying a gesture image represented by the optimal gesture template. 5. The gesture recognition system according to claim 1 , wherein the skin part is filtered from the image by using a skin processing method, and the skin edge of the skin part is found out with an edge detector. | 0.88999 |
9,418,113 | 1 | 2 | 1. A computer-implemented method, comprising: receiving a continuous input data stream related to an application; generating an input relation from the continuous input data stream, the input relation being a bounded set of data records of the continuous input data stream; storing the input relation as an external data source in a database of historical data; receiving a continuous query that identifies the input relation and a range value window operator associated with the input relation; executing the continuous query to generate an output relation, the continuous query executed by applying the range value window operator on an attribute of the input relation to generate the output relation, the attribute comprising a characteristic of an event associated with the input relation; determining whether the event associated with the input relation occurs within a specified time range defined by the range value window operator; inserting or removing the event with respect to the output relation based at least in part on the determination of whether the event associated with the input relation occurs within the specified time range; and providing data records of the output relation, the output relation comprising at least the event when the event was inserted based at least in part on being within the specified range defined by the range value window operator. | 1. A computer-implemented method, comprising: receiving a continuous input data stream related to an application; generating an input relation from the continuous input data stream, the input relation being a bounded set of data records of the continuous input data stream; storing the input relation as an external data source in a database of historical data; receiving a continuous query that identifies the input relation and a range value window operator associated with the input relation; executing the continuous query to generate an output relation, the continuous query executed by applying the range value window operator on an attribute of the input relation to generate the output relation, the attribute comprising a characteristic of an event associated with the input relation; determining whether the event associated with the input relation occurs within a specified time range defined by the range value window operator; inserting or removing the event with respect to the output relation based at least in part on the determination of whether the event associated with the input relation occurs within the specified time range; and providing data records of the output relation, the output relation comprising at least the event when the event was inserted based at least in part on being within the specified range defined by the range value window operator. 2. The computer-implemented method of claim 1 , wherein the input relation is generated based at least in part on information related to the application. | 0.896622 |
10,146,770 | 8 | 12 | 8. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to implement a cognitive system for capturing referential information, wherein the computer readable program causes the computing device to: receive, by a message aggregator executing within the cognitive system, a first indication that a group text messaging conversation is in a muted state for a first user, detect, by a cognitive agent executing within the cognitive system, a first use of a referential phrase in the group text messaging conversation during a first time period when the group text messaging conversation is in the muted state wherein detecting the first use of the referential phrase comprises: parsing, by a parser executing within the cognitive agent, one or more conversation message within the group text messaging conversation to perform parsing and semantic analysis to annotate the one or more conversation messages; extracting, by a feature extraction component executing within the cognitive agent, a set of features from the one or more conversation message describing the one or more conversation message; and processing by a natural language classifier component executing within the cognitive agent, the set of features to identify that the one or more conversation messages contain the first use of the referential phrase using a machine learning model that determines a category for each term or phrase based on the set of features and calculates a confidence for each category; receive, by the message aggregator, a second indication that the group text messaging conversation is in a non-muted state for the first user; detect, by the cognitive agent, a second use of the referential phrase in the group text messaging conversation during a second time period when the group text messaging conversation is in the non-muted state, wherein the second time period is subsequent to the first time period; alter, by the cognitive agent, a message containing the second use of the referential phrase within the group text messaging conversation within a multi-user chat display; determine, by the cognitive system, a first probability that the first user understands the referential phrase; and provide, by the cognitive system, first information to the first user within the multi-user chat display when the first probability is below a threshold, wherein the first information pertains to the referential phrase. | 8. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to implement a cognitive system for capturing referential information, wherein the computer readable program causes the computing device to: receive, by a message aggregator executing within the cognitive system, a first indication that a group text messaging conversation is in a muted state for a first user, detect, by a cognitive agent executing within the cognitive system, a first use of a referential phrase in the group text messaging conversation during a first time period when the group text messaging conversation is in the muted state wherein detecting the first use of the referential phrase comprises: parsing, by a parser executing within the cognitive agent, one or more conversation message within the group text messaging conversation to perform parsing and semantic analysis to annotate the one or more conversation messages; extracting, by a feature extraction component executing within the cognitive agent, a set of features from the one or more conversation message describing the one or more conversation message; and processing by a natural language classifier component executing within the cognitive agent, the set of features to identify that the one or more conversation messages contain the first use of the referential phrase using a machine learning model that determines a category for each term or phrase based on the set of features and calculates a confidence for each category; receive, by the message aggregator, a second indication that the group text messaging conversation is in a non-muted state for the first user; detect, by the cognitive agent, a second use of the referential phrase in the group text messaging conversation during a second time period when the group text messaging conversation is in the non-muted state, wherein the second time period is subsequent to the first time period; alter, by the cognitive agent, a message containing the second use of the referential phrase within the group text messaging conversation within a multi-user chat display; determine, by the cognitive system, a first probability that the first user understands the referential phrase; and provide, by the cognitive system, first information to the first user within the multi-user chat display when the first probability is below a threshold, wherein the first information pertains to the referential phrase. 12. The computer program product of claim 8 , wherein detecting the first use of the referential phrase comprises identifying a reference to an external source of information, identifying a topic of clarifying questions in the group text messaging conversation, identifying multiple versions of an entity in the group text messaging conversation, or identifying a phrase with uniqueness and post-frequency. | 0.501229 |
8,332,221 | 10 | 17 | 10. A system comprising at least one processor programmed to: process an unstructured text to generate a first structured text comprising a plurality of text sections; assign a topic to at least one text section of the plurality of text sections; provide the first structured text to a user for review in a manner that associates the at least one text section with a section heading corresponding to the topic assigned to the at least one text section; receive input from the user indicating at least one modification to the first structured text; process the at least one modification to generate a second structured text; and provide the second structured text to the user for review. | 10. A system comprising at least one processor programmed to: process an unstructured text to generate a first structured text comprising a plurality of text sections; assign a topic to at least one text section of the plurality of text sections; provide the first structured text to a user for review in a manner that associates the at least one text section with a section heading corresponding to the topic assigned to the at least one text section; receive input from the user indicating at least one modification to the first structured text; process the at least one modification to generate a second structured text; and provide the second structured text to the user for review. 17. The system of claim 10 , wherein the at least one text section is a first text section, and wherein the at least one processor is programmed to generate the first structured text at least in part by inserting a label to define a boundary between the first text section and a second text section immediately preceding the first text section. | 0.787129 |
8,156,144 | 11 | 15 | 11. A metadata search interface system comprising: a first component for accessing a configuration file for said metadata search interface and determining a display element corresponding to a predicate of a query, said first component further for displaying said display element in said metadata search interface, said predicate supporting full text searches and corresponding to a where clause that supports multiple nested predicate types; and a second component at least partially executed by a processor for accessing a value describing a search parameter and for accessing a control associated with said predicate which describes a correlation between said value and said predicate of said metadata search interface, said second component further for automatically generating a metadata query based upon said predicate and said value. | 11. A metadata search interface system comprising: a first component for accessing a configuration file for said metadata search interface and determining a display element corresponding to a predicate of a query, said first component further for displaying said display element in said metadata search interface, said predicate supporting full text searches and corresponding to a where clause that supports multiple nested predicate types; and a second component at least partially executed by a processor for accessing a value describing a search parameter and for accessing a control associated with said predicate which describes a correlation between said value and said predicate of said metadata search interface, said second component further for automatically generating a metadata query based upon said predicate and said value. 15. The metadata search interface system of claim 11 wherein said first component dynamically creates said metadata search interface in runtime by accessing at least one of said control via a reflection library. | 0.819039 |
8,930,286 | 1 | 2 | 1. An information processing apparatus which creates a classifier for classifying an attribute of a pattern image using a plurality of nodes consisting of a tree structure, comprising: an input unit configured to input a plurality of learning pattern images to each of the plurality of nodes, each of the plurality of learning pattern images including a target object; a selection unit configured to select, from each of the plurality of learning pattern images inputted to the node, at least one point; a determination unit configured to determine, for each of the plurality of learning pattern images inputted to the node, whether the selected point belongs to a region of the target object in the learning pattern image; a distribution unit configured to distribute and input, to a lower node of each node, a learning pattern image for which said determination unit has determined that the selected point belongs to the region; a deletion unit configured to delete a learning pattern image for which said determination unit has determined that the selected point does not belong to the region; and a storage unit configured to store an attribute of the learning pattern image input to a terminal node of the plurality of nodes in association with the node, wherein said selection unit selects, from each of the plurality of learning pattern images inputted to the node, a plurality of points, said determination unit determines, for each of the plurality of learning pattern images inputted to the node, whether a ratio of the selected plurality of points belonging to the region of the target object in the learning pattern image is larger than a threshold, said distribution unit distributes and inputs, to a lower node of each node, a learning pattern image for which said determination unit has determined that the ratio of the selected plurality of points belonging to the region of the target object in the learning pattern image is larger than the threshold, and said deletion unit deletes a learning pattern image for which said determination unit has determined that the ratio of the selected plurality of points belonging to the region of the target object in the learning pattern image is not larger than the threshold. | 1. An information processing apparatus which creates a classifier for classifying an attribute of a pattern image using a plurality of nodes consisting of a tree structure, comprising: an input unit configured to input a plurality of learning pattern images to each of the plurality of nodes, each of the plurality of learning pattern images including a target object; a selection unit configured to select, from each of the plurality of learning pattern images inputted to the node, at least one point; a determination unit configured to determine, for each of the plurality of learning pattern images inputted to the node, whether the selected point belongs to a region of the target object in the learning pattern image; a distribution unit configured to distribute and input, to a lower node of each node, a learning pattern image for which said determination unit has determined that the selected point belongs to the region; a deletion unit configured to delete a learning pattern image for which said determination unit has determined that the selected point does not belong to the region; and a storage unit configured to store an attribute of the learning pattern image input to a terminal node of the plurality of nodes in association with the node, wherein said selection unit selects, from each of the plurality of learning pattern images inputted to the node, a plurality of points, said determination unit determines, for each of the plurality of learning pattern images inputted to the node, whether a ratio of the selected plurality of points belonging to the region of the target object in the learning pattern image is larger than a threshold, said distribution unit distributes and inputs, to a lower node of each node, a learning pattern image for which said determination unit has determined that the ratio of the selected plurality of points belonging to the region of the target object in the learning pattern image is larger than the threshold, and said deletion unit deletes a learning pattern image for which said determination unit has determined that the ratio of the selected plurality of points belonging to the region of the target object in the learning pattern image is not larger than the threshold. 2. The apparatus according to claim 1 , further comprising: a recognition unit configured to input, to a root node, a set of patterns to undergo pattern recognition, and to recognize a pattern by executing a query created for each node while tracing the plurality of nodes. | 0.613314 |
8,545,299 | 3 | 4 | 3. The method of claim 1 , further comprising: receiving, from the first player, an improvement feature request identifying an improvement feature to be applied to the computer-generated crossword puzzle; and applying the improvement feature identified by the improvement feature request to the computer-generated crossword puzzle, wherein the improvement feature provides additional information to derive the first solution. | 3. The method of claim 1 , further comprising: receiving, from the first player, an improvement feature request identifying an improvement feature to be applied to the computer-generated crossword puzzle; and applying the improvement feature identified by the improvement feature request to the computer-generated crossword puzzle, wherein the improvement feature provides additional information to derive the first solution. 4. The method of claim 3 , wherein the improvement feature includes providing the first player with a confidence character to denote a level of certitude in an entered solution. | 0.883706 |
7,761,590 | 9 | 12 | 9. An apparatus comprising a processor and a memory including computer program code, the memory and the computer program code configured to, with the processor, cause the apparatus at least to: receive data in a first form markup language comprising full XForms standard, the received data being intended for a client device; adapt portions of the received data which are incompatible with the client device into a second form markup language comprising XForms Basic that is compatible with the client device; capture reply data from the client device in order to validate the reply data; and send an error message to the client device in response to the reply data failing to validate and communicate the reply data to a server providing the data in the first markup language in response to the reply data validating, wherein the memory and computer program code are further configured to, with the processor, replace validation elements in the first form markup language with corresponding constraints in the second form markup language based on a mapping for conversion between Schema data types in full Xforms standard to corresponding constraints, and wherein the mapping includes providing a bind element to designate an XForms Basic data type and additional constraint corresponding to each Schema data type. | 9. An apparatus comprising a processor and a memory including computer program code, the memory and the computer program code configured to, with the processor, cause the apparatus at least to: receive data in a first form markup language comprising full XForms standard, the received data being intended for a client device; adapt portions of the received data which are incompatible with the client device into a second form markup language comprising XForms Basic that is compatible with the client device; capture reply data from the client device in order to validate the reply data; and send an error message to the client device in response to the reply data failing to validate and communicate the reply data to a server providing the data in the first markup language in response to the reply data validating, wherein the memory and computer program code are further configured to, with the processor, replace validation elements in the first form markup language with corresponding constraints in the second form markup language based on a mapping for conversion between Schema data types in full Xforms standard to corresponding constraints, and wherein the mapping includes providing a bind element to designate an XForms Basic data type and additional constraint corresponding to each Schema data type. 12. An apparatus according to claim 9 , wherein the memory and computer program code are further configured to, with the processor, cause the apparatus to determine whether the received data includes data types that are not supported in XForms Basic prior to adapting portions of the received data. | 0.600536 |
9,754,014 | 13 | 15 | 13. The computer program product of claim 10 , further comprising program instructions executable by a computer to generate a second binary decision model by training the binary classifier using the plurality of training documents and the confirmation or the negation of the classification label of the most relevant example of the classified test documents. | 13. The computer program product of claim 10 , further comprising program instructions executable by a computer to generate a second binary decision model by training the binary classifier using the plurality of training documents and the confirmation or the negation of the classification label of the most relevant example of the classified test documents. 15. The computer program product of claim 13 , wherein the confirmation or the negation of the classification label of the most relevant example of the classified test documents is the single example of user input used in generating the second binary decision model. | 0.908022 |
8,074,199 | 2 | 3 | 2. The computer-implemented system of claim 1 , wherein the UM software component comprises a setting of the UM application, the XML feature comprises a conditional attribute predetermining a transition of the UM FSM. | 2. The computer-implemented system of claim 1 , wherein the UM software component comprises a setting of the UM application, the XML feature comprises a conditional attribute predetermining a transition of the UM FSM. 3. The computer-implemented system of claim 2 , wherein the conditional attribute comprises an attribute composed of a context variable. | 0.949442 |
9,087,053 | 6 | 15 | 6. A computer-implemented method of providing document data from a document management system for display on an interface of a computer system through an enabler application that manages associations between fields of a host application and fields of documents in the document management system, comprising: displaying the host application on the interface of the computer system that includes one or more data processors and one or more non-transitory computer-readable mediums including instructions for commanding the one or more data processors, wherein the host application includes an interface field that is linked to a document field of documents in the document management system; capturing a field value for the interface field and an operation identification from the host application using the enabler application on the computer system, wherein the field value entered in the host application is captured at the enabler application without receiving any communication from the host application; accessing a context rule in a context rule database using the computer system based upon the operation identification, wherein the context rule identifies a type of document that is relevant to the identified operation; querying the document management system using the computer system based on the field value that is captured from the interface field of the host application and the relevant document type identified by the context rule that is accessed based on the operation identification from the host application; receiving document data from the document management system based on said querying using the computer system; and updating the interface of the computer system based on the document data. | 6. A computer-implemented method of providing document data from a document management system for display on an interface of a computer system through an enabler application that manages associations between fields of a host application and fields of documents in the document management system, comprising: displaying the host application on the interface of the computer system that includes one or more data processors and one or more non-transitory computer-readable mediums including instructions for commanding the one or more data processors, wherein the host application includes an interface field that is linked to a document field of documents in the document management system; capturing a field value for the interface field and an operation identification from the host application using the enabler application on the computer system, wherein the field value entered in the host application is captured at the enabler application without receiving any communication from the host application; accessing a context rule in a context rule database using the computer system based upon the operation identification, wherein the context rule identifies a type of document that is relevant to the identified operation; querying the document management system using the computer system based on the field value that is captured from the interface field of the host application and the relevant document type identified by the context rule that is accessed based on the operation identification from the host application; receiving document data from the document management system based on said querying using the computer system; and updating the interface of the computer system based on the document data. 15. The method of claim 6 , wherein the context rule identifies a plurality of relevant document types using a linked list. | 0.822254 |
10,008,203 | 1 | 6 | 1. A computer-implemented method comprising: receiving data specifying a new voice action, the data identifying (i) an application, (ii) a voice command trigger phrase for triggering the application, and (iii) a context that must be satisfied for the application to be triggered; generating a data structure instance that specifies (i) the application, (ii) the voice command trigger phrase, and (iii) an alternate voice command trigger phrase, the alternate voice command trigger phrase being based on the received voice command trigger phrase; and after generating the data structure instance, enabling triggering of the new voice action by a spoken utterance based at least on storing the data structure instance at a database that comprises a plurality of other data structure instances, wherein each of the other data structure instances specifies (i) an application, and (ii) one or more voice command trigger phrases; determining that the context is satisfied; after enabling the triggering of the new voice action and based at least on determining that a transcription of a spoken utterance includes the alternate voice command trigger phrase specified by the generated data structure instance, selecting the generated data structure instance from the database; and based on the selection of the generated data structure instance and based on the determination that the context is satisfied, causing an activity associated with the application specified by the generated data structure to be performed on or by the application. | 1. A computer-implemented method comprising: receiving data specifying a new voice action, the data identifying (i) an application, (ii) a voice command trigger phrase for triggering the application, and (iii) a context that must be satisfied for the application to be triggered; generating a data structure instance that specifies (i) the application, (ii) the voice command trigger phrase, and (iii) an alternate voice command trigger phrase, the alternate voice command trigger phrase being based on the received voice command trigger phrase; and after generating the data structure instance, enabling triggering of the new voice action by a spoken utterance based at least on storing the data structure instance at a database that comprises a plurality of other data structure instances, wherein each of the other data structure instances specifies (i) an application, and (ii) one or more voice command trigger phrases; determining that the context is satisfied; after enabling the triggering of the new voice action and based at least on determining that a transcription of a spoken utterance includes the alternate voice command trigger phrase specified by the generated data structure instance, selecting the generated data structure instance from the database; and based on the selection of the generated data structure instance and based on the determination that the context is satisfied, causing an activity associated with the application specified by the generated data structure to be performed on or by the application. 6. The computer-implemented method of claim 1 , wherein the received voice command trigger phrase includes a placeholder term that may be replaced by one or more other terms, and wherein generating the alternate voice command trigger phrase includes determining an alternate voice command trigger phrase that includes a variant of the placeholder term. | 0.805525 |
9,141,689 | 1 | 7 | 1. A computer program product comprising a computer useable storage device to store a computer readable program that, when executed on a processor within a computer, causes the computer to perform operations to apply persona styles to written communications, the operations comprising: identify an element of original content of a written communication; determine that the element of the original content of the written communication is incompatible with a selected persona style, wherein the selected persona style defines a communication style; identify a substitute element, wherein the substitute element is identified based on a compatibility between the substitute element and the selected persona style; propose the substitute element for replacement of the element of the original content for consideration by an author of the original content of the written communication; and modify the original content of the written communication to replace the element of the original content with the substitute element. | 1. A computer program product comprising a computer useable storage device to store a computer readable program that, when executed on a processor within a computer, causes the computer to perform operations to apply persona styles to written communications, the operations comprising: identify an element of original content of a written communication; determine that the element of the original content of the written communication is incompatible with a selected persona style, wherein the selected persona style defines a communication style; identify a substitute element, wherein the substitute element is identified based on a compatibility between the substitute element and the selected persona style; propose the substitute element for replacement of the element of the original content for consideration by an author of the original content of the written communication; and modify the original content of the written communication to replace the element of the original content with the substitute element. 7. The computer program product of claim 1 , wherein the computer readable program, when executed on the computer, causes the computer to perform an operation to store a sentence template, wherein the sentence template comprises a fill-in-the-blank sentence for completion by a user. | 0.739411 |
9,478,219 | 7 | 8 | 7. The method of claim 1 wherein when a user selects text, the one or more computer systems begin playback at the first word in the user-selected text and reads continuously from that point. | 7. The method of claim 1 wherein when a user selects text, the one or more computer systems begin playback at the first word in the user-selected text and reads continuously from that point. 8. The method of claim 7 wherein the one or more computer systems stop playback according to at least one of when the user inputs a command to the system to stop, when the system reaches the end of the document, when the system reaches the end of the user selected portion of the document, and when the system reaches a preset configuration selected from playback of a single paragraph, a single syllable, word, sentence, page, or other part of speech or reading unit. | 0.852366 |
7,801,909 | 1 | 11 | 1. An apparatus for identifying potential patent infringement, comprising: means for inputting information regarding a patent; a processing device configured to: identify at least one claim of the patent, parse the at least one claim to identify at least one term in the at least one claim, formulate a search query comprising the at least one term, automatically generate and transmit a natural language question to a chat room, obtain information regarding at least one of a product, products, a service, and services from the chat room in response to the question, and perform a search of the information regarding at least one of a product, products, a service, and services using the search query; and means for outputting result of the search. | 1. An apparatus for identifying potential patent infringement, comprising: means for inputting information regarding a patent; a processing device configured to: identify at least one claim of the patent, parse the at least one claim to identify at least one term in the at least one claim, formulate a search query comprising the at least one term, automatically generate and transmit a natural language question to a chat room, obtain information regarding at least one of a product, products, a service, and services from the chat room in response to the question, and perform a search of the information regarding at least one of a product, products, a service, and services using the search query; and means for outputting result of the search. 11. The apparatus of claim 1 , wherein the search query further contains a synonym of the at least one term. | 0.930858 |
8,983,038 | 7 | 8 | 7. An apparatus configured to process spoken words received from a user of a calling platform, the apparatus comprising: a call processing unit configured to call a user; a transmitter configured to transmit a call prompt message to the user after the user has answered the call, the call prompt message soliciting a user response; a receiver configured to receive a spoken call greeting from the user in response to the call prompt message, the spoken call greeting comprising at least one initial utterance; a memory configured to record the spoken call greeting and the at least one initial utterance; and a processor configured to perform an initial determination as to whether the at least one initial utterance of the spoken call greeting is indicative of a language preference via a first language preference characterization operation, assign an initial numerical confidence level value to the at least one initial utterance by retrieving and matching at least one pre-stored word or phrase to the at least one initial utterance, wherein the initial numerical confidence level is based on a relative strength of the at least one initial utterance being indicative of the language preference, and confirm the initial determination based on at least one additional utterance spoken after the at least one initial utterance by performing at least one additional language preference characterization operation to the at least one additional utterance spoken. | 7. An apparatus configured to process spoken words received from a user of a calling platform, the apparatus comprising: a call processing unit configured to call a user; a transmitter configured to transmit a call prompt message to the user after the user has answered the call, the call prompt message soliciting a user response; a receiver configured to receive a spoken call greeting from the user in response to the call prompt message, the spoken call greeting comprising at least one initial utterance; a memory configured to record the spoken call greeting and the at least one initial utterance; and a processor configured to perform an initial determination as to whether the at least one initial utterance of the spoken call greeting is indicative of a language preference via a first language preference characterization operation, assign an initial numerical confidence level value to the at least one initial utterance by retrieving and matching at least one pre-stored word or phrase to the at least one initial utterance, wherein the initial numerical confidence level is based on a relative strength of the at least one initial utterance being indicative of the language preference, and confirm the initial determination based on at least one additional utterance spoken after the at least one initial utterance by performing at least one additional language preference characterization operation to the at least one additional utterance spoken. 8. The apparatus of claim 7 , wherein the call processing unit is configured to call the user automatically without live agent interaction. | 0.840961 |
7,865,016 | 1 | 14 | 1. A computer implemented method for recognition of a handwritten pattern comprising one or more curves, said method comprising: receiving, by a computational device, sample data representing the handwritten pattern; segmenting, by the computational device, the handwritten pattern by detecting segmentation points on each curve and by dividing the handwritten pattern into segments, wherein detecting segmentation points further comprises detecting the segmentation points as local extreme points which are below a predetermined threshold, such that a particular gradient function of the curve is exceeded; and comparing, by the computational device, the handwritten pattern to templates wherein the comparing comprises: normalizing, by the computational device, said segments according to a scheme which is independent of the templates to which the segments are to be compared, and determining, by the computational device, matching measures for selecting at least one sequence of templates representing a recognition candidate of the handwritten pattern. | 1. A computer implemented method for recognition of a handwritten pattern comprising one or more curves, said method comprising: receiving, by a computational device, sample data representing the handwritten pattern; segmenting, by the computational device, the handwritten pattern by detecting segmentation points on each curve and by dividing the handwritten pattern into segments, wherein detecting segmentation points further comprises detecting the segmentation points as local extreme points which are below a predetermined threshold, such that a particular gradient function of the curve is exceeded; and comparing, by the computational device, the handwritten pattern to templates wherein the comparing comprises: normalizing, by the computational device, said segments according to a scheme which is independent of the templates to which the segments are to be compared, and determining, by the computational device, matching measures for selecting at least one sequence of templates representing a recognition candidate of the handwritten pattern. 14. The computer implemented method according to claim 1 , further comprising a step of associating, by the computational device, an output weight to normalized segmental and connective features. | 0.590336 |
7,523,390 | 9 | 13 | 9. An apparatus comprising: one or more processors; and one or more computer-readable media having computer-executable instructions therein that are configured, when executed by the one or more processors, to: display a first free floating field, a second free floating field, and text from a document written in eXtensible Markup Language (XML); determine a type of content already in the first free floating field; display a first user interface if the first type of content determined to already be in the first free floating field is a formula and display a second user interface if the first type of content determined to already be in the free floating field is text, wherein the first user interface is distinct from the second user interface, the first user interface being associated with formula entry and the second user interface being associated with text entry; receive first additional content entered into the first free floating field by a user; interpret the first additional content based upon the first type of content already in the first free floating field, as determined; automatically recalculate any formulas within the document, as needed, upon receipt of the first additional content; determine that a second type of content already in the second free floating field is a different type than the first type; display the other of the first user interface and the second user interface not displayed; receive second additional content entered into the second free floating field by the user; interpret the second additional content based on the second type of content already in the second free floating field, as determined; and automatically recalculate any formulas within the document, as needed, upon receipt of the second additional content. | 9. An apparatus comprising: one or more processors; and one or more computer-readable media having computer-executable instructions therein that are configured, when executed by the one or more processors, to: display a first free floating field, a second free floating field, and text from a document written in eXtensible Markup Language (XML); determine a type of content already in the first free floating field; display a first user interface if the first type of content determined to already be in the first free floating field is a formula and display a second user interface if the first type of content determined to already be in the free floating field is text, wherein the first user interface is distinct from the second user interface, the first user interface being associated with formula entry and the second user interface being associated with text entry; receive first additional content entered into the first free floating field by a user; interpret the first additional content based upon the first type of content already in the first free floating field, as determined; automatically recalculate any formulas within the document, as needed, upon receipt of the first additional content; determine that a second type of content already in the second free floating field is a different type than the first type; display the other of the first user interface and the second user interface not displayed; receive second additional content entered into the second free floating field by the user; interpret the second additional content based on the second type of content already in the second free floating field, as determined; and automatically recalculate any formulas within the document, as needed, upon receipt of the second additional content. 13. The apparatus of claim 9 , wherein a first formula is in the first free floating field, the apparatus further comprising instructions configured to: display a third free floating field in the document; enable the user to enter a second formula into the third free floating field, the second formula referencing the first free floating field; and upon modification of one of the first and third free floating fields, automatically recalculate the other of the first and third free floating fields. | 0.531835 |
8,627,276 | 51 | 55 | 51. The device of claim 50 , where the first part includes a portion of the graphical model and the second part includes a segment of the code. | 51. The device of claim 50 , where the first part includes a portion of the graphical model and the second part includes a segment of the code. 55. The device of claim 51 , where the processor is further to: search the code for the segment; and graphically relate the segment with the portion. | 0.969316 |
8,290,977 | 60 | 69 | 60. In a database system, a method for executing an XPath built-in function in an XPath-based query requesting data from an Extensible Markup Language (XML) document, the method comprising: receiving the XPath-based query requesting data from an XML document, the XPath-based query including an XPath built-in function to be executed on data from an XML document which includes a plurality of hierarchically arranged elements, said XPath built-in function operating within a particular context of the XML document during execution of the XPath-based query; during execution of the XPath-based query: determining elements of the XML document satisfying the XPath- based query, obtaining values of said elements of the XML document, associating said values with elements of the XML document, and executing the XPath built-in function with said values and associated elements. | 60. In a database system, a method for executing an XPath built-in function in an XPath-based query requesting data from an Extensible Markup Language (XML) document, the method comprising: receiving the XPath-based query requesting data from an XML document, the XPath-based query including an XPath built-in function to be executed on data from an XML document which includes a plurality of hierarchically arranged elements, said XPath built-in function operating within a particular context of the XML document during execution of the XPath-based query; during execution of the XPath-based query: determining elements of the XML document satisfying the XPath- based query, obtaining values of said elements of the XML document, associating said values with elements of the XML document, and executing the XPath built-in function with said values and associated elements. 69. The method of claim 60 , wherein said determining step includes parsing the query to create an in-memory representation of the query in tree form. | 0.815271 |
8,645,421 | 15 | 16 | 15. A system for providing data records, comprising: one or more processors; one or more computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: accessing a physical hierarchy, wherein the physical hierarchy represents organizational data, wherein the physical hierarchy includes a plurality of transactional data records that are hierarchically arranged in levels, wherein the plurality of records include fields, wherein the fields include physical hierarchy fields and attribute hierarchy fields, and wherein each level in the physical hierarchy corresponds to a physical hierarchy field; identifying one or more attribute hierarchy fields within the plurality of records included in the physical hierarchy, wherein the one or more attribute hierarchy fields correspond to input fields of a predictive model; generating an attribute hierarchy using the physical hierarchy, wherein the attribute hierarchy includes the plurality of records in the physical hierarchy re-categorized according to the one or more identified attribute hierarchy fields, wherein the attribute hierarchy includes one or more new levels, wherein the one or more new levels are new with respect to the physical hierarchy, and wherein each new level in the attribute hierarchy corresponds to an identified attribute hierarchy field; generating a mapping table that identifies levels of the physical hierarchy and levels of the attribute hierarchy; receiving a request from the predictive model, wherein the request specifies one or more records from a particular new level in the attribute hierarchy; providing the one or more records from the particular new level to the predictive model; and processing the one or more records, wherein the one or more records are provided to the predictive model for generating estimation results or forecasting results. | 15. A system for providing data records, comprising: one or more processors; one or more computer-readable storage mediums containing instructions configured to cause the one or more processors to perform operations including: accessing a physical hierarchy, wherein the physical hierarchy represents organizational data, wherein the physical hierarchy includes a plurality of transactional data records that are hierarchically arranged in levels, wherein the plurality of records include fields, wherein the fields include physical hierarchy fields and attribute hierarchy fields, and wherein each level in the physical hierarchy corresponds to a physical hierarchy field; identifying one or more attribute hierarchy fields within the plurality of records included in the physical hierarchy, wherein the one or more attribute hierarchy fields correspond to input fields of a predictive model; generating an attribute hierarchy using the physical hierarchy, wherein the attribute hierarchy includes the plurality of records in the physical hierarchy re-categorized according to the one or more identified attribute hierarchy fields, wherein the attribute hierarchy includes one or more new levels, wherein the one or more new levels are new with respect to the physical hierarchy, and wherein each new level in the attribute hierarchy corresponds to an identified attribute hierarchy field; generating a mapping table that identifies levels of the physical hierarchy and levels of the attribute hierarchy; receiving a request from the predictive model, wherein the request specifies one or more records from a particular new level in the attribute hierarchy; providing the one or more records from the particular new level to the predictive model; and processing the one or more records, wherein the one or more records are provided to the predictive model for generating estimation results or forecasting results. 16. The system of claim 15 , wherein the operations further include: using the mapping table to recreate the attribute hierarchy when a significant change occurs in the physical hierarchy or the attribute hierarchy. | 0.631849 |
9,667,788 | 19 | 25 | 19. A method for analyzing electronic customer communication data, generating behavioral assessment data and generating a responsive communication, which method comprises: receiving, by a server, electronic customer communication data of two or more types, wherein the server is configured to provide a user interface comprising a web site, web portal, or virtual portal, and wherein at least one of the two or more types of electronic customer communication data comprises social media data, update status, media feed, social media review, social media data stream, social media profile or social media account setup; identifying a customer associated with the electronic customer communication data received by the server; aggregating electronic customer communication data from one or more sources based on identification of the customer from the electronic customer communication data; analyzing the aggregated electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data for that identified customer; generating behavioral assessment data by the contact center based on said analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data for that identified customer; generating a responsive communication based on the generated behavioral assessment data; and providing the responsive communication via the user interface. | 19. A method for analyzing electronic customer communication data, generating behavioral assessment data and generating a responsive communication, which method comprises: receiving, by a server, electronic customer communication data of two or more types, wherein the server is configured to provide a user interface comprising a web site, web portal, or virtual portal, and wherein at least one of the two or more types of electronic customer communication data comprises social media data, update status, media feed, social media review, social media data stream, social media profile or social media account setup; identifying a customer associated with the electronic customer communication data received by the server; aggregating electronic customer communication data from one or more sources based on identification of the customer from the electronic customer communication data; analyzing the aggregated electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data for that identified customer; generating behavioral assessment data by the contact center based on said analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data for that identified customer; generating a responsive communication based on the generated behavioral assessment data; and providing the responsive communication via the user interface. 25. The method of claim 19 , wherein the generated behavioral assessment data is associated with at least one identifying indicia. | 0.809942 |
9,413,771 | 1 | 2 | 1. A method comprising: providing a system comprising unencrypted and encrypted document content, wherein an unencrypted document is encrypted to become an encrypted document, and the encrypted document is larger in size than the unencrypted document from which it is derived; providing a policy server accessible to devices of the system, wherein the policy server comprises a plurality of policies and each policy manages access to documents of the system; providing an encryption service driver executing on a computing device of the devices of the system, wherein the policy server is separate from the computing device; permitting access to an encrypted document by an application program on the computing device; when an access to the encrypted document occurs, using the encryption service to intercept the access of the encrypted document, wherein the intercepting the access of the encrypted document occurs at a system level of the application program comprising: allowing the access to the encrypted document by the application program to execute until a first system level operation executes; identifying the first system level operation as executing due to the application program requesting access to the encrypted document; preventing the first system level operation from executing; at the encryption service, identifying the application program attempting to access the encrypted document; from the encryption service, sending identification information on the application program to a policy enforcer component, executing on the computing device; controlling access to the unencrypted content based on the first policy comprising: identifying a first application process identifier assigned by an operating system executing on the computing device for the application program, wherein the application program is attempting access to the encrypted document; receiving a decryption key based on the first application process identifier at the encryption service; using the encryption service to decrypt the encrypted document to produce the unencrypted content; providing the unencrypted content to the application program; and allowing the first system level operation to execute. | 1. A method comprising: providing a system comprising unencrypted and encrypted document content, wherein an unencrypted document is encrypted to become an encrypted document, and the encrypted document is larger in size than the unencrypted document from which it is derived; providing a policy server accessible to devices of the system, wherein the policy server comprises a plurality of policies and each policy manages access to documents of the system; providing an encryption service driver executing on a computing device of the devices of the system, wherein the policy server is separate from the computing device; permitting access to an encrypted document by an application program on the computing device; when an access to the encrypted document occurs, using the encryption service to intercept the access of the encrypted document, wherein the intercepting the access of the encrypted document occurs at a system level of the application program comprising: allowing the access to the encrypted document by the application program to execute until a first system level operation executes; identifying the first system level operation as executing due to the application program requesting access to the encrypted document; preventing the first system level operation from executing; at the encryption service, identifying the application program attempting to access the encrypted document; from the encryption service, sending identification information on the application program to a policy enforcer component, executing on the computing device; controlling access to the unencrypted content based on the first policy comprising: identifying a first application process identifier assigned by an operating system executing on the computing device for the application program, wherein the application program is attempting access to the encrypted document; receiving a decryption key based on the first application process identifier at the encryption service; using the encryption service to decrypt the encrypted document to produce the unencrypted content; providing the unencrypted content to the application program; and allowing the first system level operation to execute. 2. The method of claim 1 comprising: if the application program is determined not to be trusted, providing encrypted content of the encrypted document to the application program. | 0.814969 |
7,930,180 | 9 | 10 | 9. A non-transitory computer readable medium storing a speech recognition program causing a computer constituting a speech recognition system to perform: a function of generating a distance value between the speech feature, inputted sequentially, and each acoustic model; a function of generating an acoustic lookahead value by using the distance value previously generated when the distance values are continuously generated; and a function of performing word string matching by using the distance value previously generated and the acoustic lookahead value previously generated, and generating a recognition result when the distance values are continuously generated and when the acoustic lookahead values are continuously generated. | 9. A non-transitory computer readable medium storing a speech recognition program causing a computer constituting a speech recognition system to perform: a function of generating a distance value between the speech feature, inputted sequentially, and each acoustic model; a function of generating an acoustic lookahead value by using the distance value previously generated when the distance values are continuously generated; and a function of performing word string matching by using the distance value previously generated and the acoustic lookahead value previously generated, and generating a recognition result when the distance values are continuously generated and when the acoustic lookahead values are continuously generated. 10. The non-transitory computer readable medium, according to claim 9 , causing functions of distance value buffers for reading and writing the distance values generated and functions of acoustic lookahead value buffers for reading and writing the acoustic lookahead values generated to be performed, causing functions of reading and writing by the distance value buffers to be performed in parallel, and causing functions of reading and writing by the acoustic lookahead value buffers to be performed in parallel; wherein, at any point in time, the distance value buffer in which the distance value from the distance calculation unit is written, the distance value buffer from which the distance value to the acoustic lookahead unit is read out, and the distance value buffer from which the distance value to the word string matching unit are read out, are difference from one another, and wherein the acoustic lookahead value buffer in which the acoustic lookahead value from the acoustic lookahead unit is written and the acoustic lookahead value buffer from which the acoustic lookahead value to the word string matching unit is read out are different from each other. | 0.734481 |
8,296,288 | 1 | 3 | 1. A computer-implemented method for processing user entered query data to improve results of a search of pages using a database, when searching the internet, comprising: (a) receiving, via a special purpose computing apparatus, the user entered query data and parsing each word of the query data; (b) segmenting words using a probability to determine a likelihood that the word is for a particular name, and associating the particular names with a name tag to create one or more tagged name terms, (c) normalizing each of the tagged name terms and the normalizing including boosting information if found in the database, determining proximity between selected ones of the tagged name terms; and (d) generating an optimized search query that incorporates normalized terms and operators, the optimized search query being applied to the internet to enable search results to be produced and displayed to the user in response to the entered query data. | 1. A computer-implemented method for processing user entered query data to improve results of a search of pages using a database, when searching the internet, comprising: (a) receiving, via a special purpose computing apparatus, the user entered query data and parsing each word of the query data; (b) segmenting words using a probability to determine a likelihood that the word is for a particular name, and associating the particular names with a name tag to create one or more tagged name terms, (c) normalizing each of the tagged name terms and the normalizing including boosting information if found in the database, determining proximity between selected ones of the tagged name terms; and (d) generating an optimized search query that incorporates normalized terms and operators, the optimized search query being applied to the internet to enable search results to be produced and displayed to the user in response to the entered query data. 3. A computer-implemented method as recited in claim 1 , wherein the normalizing is executed in order on each of the tagged name terms. | 0.719917 |
8,346,686 | 1 | 5 | 1. A computer implemented method for modeling event data using a pre-existing taxonomy of events, the event data representing a plurality of sequences of events, each sequence comprising an order of events initiated by a corresponding user, each event mapping to a leaf node of the taxonomy, the method comprising: identifying a plurality of candidate Markov models, each Markov model representing probabilities of a user transitioning from any first node in the Markov model to any second node in the Markov model according to the sequences of events, each Markov model formed from a subset of nodes in the taxonomy by merging selected nodes of the taxonomy into corresponding ancestor nodes of the taxonomy, wherein each event is represented by a node in each Markov model, and further wherein no Markov model contains both a particular node and an ancestor of that particular node; measuring the fitness of the candidate Markov models with a fitness policy; selecting at least some of the plurality of candidate Markov models with reference to the fitness measure and one or more resource constraints; and choosing a preferred Markov model from the selected candidate Markov models with reference to an objective function. | 1. A computer implemented method for modeling event data using a pre-existing taxonomy of events, the event data representing a plurality of sequences of events, each sequence comprising an order of events initiated by a corresponding user, each event mapping to a leaf node of the taxonomy, the method comprising: identifying a plurality of candidate Markov models, each Markov model representing probabilities of a user transitioning from any first node in the Markov model to any second node in the Markov model according to the sequences of events, each Markov model formed from a subset of nodes in the taxonomy by merging selected nodes of the taxonomy into corresponding ancestor nodes of the taxonomy, wherein each event is represented by a node in each Markov model, and further wherein no Markov model contains both a particular node and an ancestor of that particular node; measuring the fitness of the candidate Markov models with a fitness policy; selecting at least some of the plurality of candidate Markov models with reference to the fitness measure and one or more resource constraints; and choosing a preferred Markov model from the selected candidate Markov models with reference to an objective function. 5. The method of claim 1 wherein selecting at least some of the candidate Markov models with reference to the fitness measure comprises selecting each selected candidate Markov model according to one of (i) a likelihood score of the selected candidate Markov model, (ii) a minimal number of nodes in the selected candidate Markov model, or (iii) an objective function score on the selected candidate Markov model. | 0.668539 |
9,110,990 | 6 | 9 | 6. The method of claim 1 , wherein calculating the result weights further comprises: calculating the result weights further based on a log file of frequently selected programs. | 6. The method of claim 1 , wherein calculating the result weights further comprises: calculating the result weights further based on a log file of frequently selected programs. 9. The method of claim 6 , wherein the log file contains search results selected by users proximate in viewing habits. | 0.96324 |
8,572,457 | 12 | 13 | 12. A method of operating a solid state memory device including multiple blocks, each block comprising an array of memory cells arranged in a plurality of pages, the method comprising: encoding data into inner code words and outer code words, the inner code words comprising data and parity information, each page of each block storing at least one inner code word, the outer code words comprising data symbols and parity symbols, one or more pages of each block storing one or more symbols of each outer code word; reading the inner code words and the outer code words from the memory device; correcting errors in the data using the inner code words and the outer code words; and providing an error corrected output from the corrected data. | 12. A method of operating a solid state memory device including multiple blocks, each block comprising an array of memory cells arranged in a plurality of pages, the method comprising: encoding data into inner code words and outer code words, the inner code words comprising data and parity information, each page of each block storing at least one inner code word, the outer code words comprising data symbols and parity symbols, one or more pages of each block storing one or more symbols of each outer code word; reading the inner code words and the outer code words from the memory device; correcting errors in the data using the inner code words and the outer code words; and providing an error corrected output from the corrected data. 13. The method of claim 12 , wherein the memory device includes multiple memory chips and each of the multiple blocks is arranged respectively on one of the multiple chips. | 0.682657 |
8,762,962 | 1 | 11 | 1. A method, executed by electronic computer hardware in combination with software, for automatic translation of a computer program language code, comprising: tokenizing one or more characters of a source programming language code to generate a list of tokens; parsing the list of tokens to generate a grammatical data structure, wherein the grammatical data structure comprises one or more data nodes; processing the one or more data nodes of the grammatical data, structure to generate a document object model, wherein the document object model comprises one or more portable data nodes; and analyzing the one or more portable data nodes in the document object model to generate one or more characters of a target programming language code; normalizing the source programming language, wherein one or more features of the source programming language are managed based on one or more features of the target programming language, comprising: identifying one or more non-equivalent and one or more equivalent features from the one or more features in the source programming language, wherein the one or more non-equivalent features and the one or more equivalent features are identified based on the one or more features of the target programming language; and removing the one or more non-equivalent features of the source programming language; wherein equivalent features are features that are configured to be mapped the source programming language and the target programming language. | 1. A method, executed by electronic computer hardware in combination with software, for automatic translation of a computer program language code, comprising: tokenizing one or more characters of a source programming language code to generate a list of tokens; parsing the list of tokens to generate a grammatical data structure, wherein the grammatical data structure comprises one or more data nodes; processing the one or more data nodes of the grammatical data, structure to generate a document object model, wherein the document object model comprises one or more portable data nodes; and analyzing the one or more portable data nodes in the document object model to generate one or more characters of a target programming language code; normalizing the source programming language, wherein one or more features of the source programming language are managed based on one or more features of the target programming language, comprising: identifying one or more non-equivalent and one or more equivalent features from the one or more features in the source programming language, wherein the one or more non-equivalent features and the one or more equivalent features are identified based on the one or more features of the target programming language; and removing the one or more non-equivalent features of the source programming language; wherein equivalent features are features that are configured to be mapped the source programming language and the target programming language. 11. The method of claim 1 , wherein analyzing the one or more portable data nodes in the document object model comprises: processing recursively the one or more portable data nodes in the document object model to generate a target list of tokens; and analyzing the target list of tokens to generate the one or more characters of the target programming language code. | 0.607296 |
9,037,460 | 13 | 15 | 13. The computer storage device of claim 11 , further comprising computing forward and backward probabilities and re-estimating the weights. | 13. The computer storage device of claim 11 , further comprising computing forward and backward probabilities and re-estimating the weights. 15. The computer-readable medium of claim 13 , wherein re-estimating the weights comprises using: λ k =({tilde over (E)}(f k )−E(f k ))·σ 2 and θ l =({tilde over (E)}(θ l )−E(θ l ))·σ 2 where The σ 2 is a preset parameter to help in avoiding over fitting, vector {tilde over (E)}(f k ) and {tilde over (E)}(θ l ) are actual expectations obtained by counting how often each feature occurs in training data and E(f k ) and E(θ f ) are the estimated expectations. | 0.829123 |
9,177,069 | 16 | 17 | 16. The method of claim 1 where determining one or more similar geographic features to the target geographic feature includes comparing a number of shared excess queries and a number of dissimilar excess queries for the target geographic feature and a candidate geographic feature. | 16. The method of claim 1 where determining one or more similar geographic features to the target geographic feature includes comparing a number of shared excess queries and a number of dissimilar excess queries for the target geographic feature and a candidate geographic feature. 17. The method of claim 16 where comparing a number of dissimilar excess queries includes determining if the number of dissimilar excess queries exceeds a dissimilarity threshold, and determining that the target geographic feature and candidate geographic feature are not similar if the number of dissimilar excess queries exceeds the dissimilarity threshold. | 0.926314 |
8,479,161 | 1 | 3 | 1. A method execute by a processor for performing software due diligence review, comprising: receiving software subject to due diligence review, wherein the received software includes at least one source file; exposing plain text information for the at least one source file; searching the plain text information for the at least one source file to identify one or more keywords relevant to the due diligence review, wherein searching the plain text information to identify the one or more keywords includes identifying one or more normal keywords that indicate language potentially relevant to the due diligence review, identifying one or more negative keywords that indicate language irrelevant to the due diligence review, wherein a threshold proximity is associated with each of the respective negative keywords, negating at least one of the normal keywords if the at least one normal keyword appears within the threshold proximity associated with one or more of the negative keywords, identifying a plurality of weak normal keywords that indicate language potentially relevant to the due diligence review, wherein a threshold value is associated with each of the respective weak normal keywords, incrementing a normal counter according to the threshold values associated with each of the respective weak normal keywords, and triggering a keyword match for the plurality of weak normal keywords if the normal counter exceeds a first threshold value; matching the identified keywords against a plurality of text patterns that contain excerpts of language relevant to the due diligence review; and constructing a report providing information relating to the due diligence review, wherein the report indicates whether the software has potential compliance problems regarding one or more of software licenses, export regulations, or internal security policies. | 1. A method execute by a processor for performing software due diligence review, comprising: receiving software subject to due diligence review, wherein the received software includes at least one source file; exposing plain text information for the at least one source file; searching the plain text information for the at least one source file to identify one or more keywords relevant to the due diligence review, wherein searching the plain text information to identify the one or more keywords includes identifying one or more normal keywords that indicate language potentially relevant to the due diligence review, identifying one or more negative keywords that indicate language irrelevant to the due diligence review, wherein a threshold proximity is associated with each of the respective negative keywords, negating at least one of the normal keywords if the at least one normal keyword appears within the threshold proximity associated with one or more of the negative keywords, identifying a plurality of weak normal keywords that indicate language potentially relevant to the due diligence review, wherein a threshold value is associated with each of the respective weak normal keywords, incrementing a normal counter according to the threshold values associated with each of the respective weak normal keywords, and triggering a keyword match for the plurality of weak normal keywords if the normal counter exceeds a first threshold value; matching the identified keywords against a plurality of text patterns that contain excerpts of language relevant to the due diligence review; and constructing a report providing information relating to the due diligence review, wherein the report indicates whether the software has potential compliance problems regarding one or more of software licenses, export regulations, or internal security policies. 3. The method of claim 1 , wherein matching the identified keywords against the plurality of text patterns includes: pre-filtering the plurality of text patterns to create a set of text patterns that potentially include language relevant to the due diligence review; generating a signature for the at least one source file; generating a signature for each of the text patterns in the set of text patterns that potentially include language relevant to the due diligence review; comparing the signature generated for the at least one source file to the signatures generated for the text patterns in the set of text patterns; and executing a multi-pattern search algorithm if one or more of the text patterns have signatures that match the signature of the source file, wherein the multi-pattern search algorithm determines whether the signature match is an actual match or a false positive. | 0.620188 |
9,152,678 | 24 | 25 | 24. The storage device of claim 21 , wherein the determined historical click-through rates are for a first geographic region. | 24. The storage device of claim 21 , wherein the determined historical click-through rates are for a first geographic region. 25. The storage device of claim 24 , 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. | 0.929123 |
8,920,469 | 2 | 5 | 2. The system of claim 1 , wherein the locking mechanism includes a threaded member that extends through the elongate opening of the connecting member and threadably engages the opposed arms of the spinal fixation element receiving portion of the bone anchor. | 2. The system of claim 1 , wherein the locking mechanism includes a threaded member that extends through the elongate opening of the connecting member and threadably engages the opposed arms of the spinal fixation element receiving portion of the bone anchor. 5. The system of claim 2 , wherein the locking mechanism includes a cap having a head and a distally extending threaded shank, the shank being configured to extend into a threaded bore formed in the threaded member. | 0.890082 |
9,519,691 | 12 | 18 | 12. A technology tracking system comprising: a network interface providing coupling over a network; a hardware processor coupled to the network interface; and electronic hardware memory coupled to the hardware processor wherein the electronic hardware memory provides a taxonomy including a plurality of software application names and a plurality of capability terms associated with the software application names, wherein for each of the capability terms, the respective capability term is associated with at least a respective one of the software application names, and wherein the electronic hardware memory comprises computer readable program code that when executed by the hardware processor causes the hardware processor to perform operations to, perform a first search of a data source using the plurality of software application names and the plurality of capability terms from the taxonomy in the electronic hardware memory, wherein the data source is a first data source, retrieve a first plurality of text segments from the data source responsive to performing the first search the data source, wherein each of the text segments includes at least one of the software application names or at least one of the capability terms from the taxonomy in the electronic hardware memory, identify at least one new software application name or at least one new capability term from the first plurality of text segments retrieved from the data source responsive to performing the first search, determine a respective use frequency for each of the at least one new software application name or for each of the at least one new capability term, wherein determining the respective use frequency for each of the at least one new software application name or for each of the at least one new capability term comprises searching a second data source for a number of instances of each of the at least one new software application name of for each of the at least one new capability term, and wherein the second data source is different than the first data source, update the taxonomy in the electronic hardware memory to include at least a first one of the at least one new software application name having the respective use frequency that is greater than the use frequency threshold or to include a first one of the at least one new capability term having the respective use frequency that is greater than the use frequency threshold; update a fringe list in the electronic hardware memory to include a second one of the at least one new software application name having a respective first use frequency that is less than the use frequency threshold or to include a second one of the at least one new capability term having a respective first use frequency that is less than the use frequency threshold, wherein the second one of the at least one new software application name or the second one of the at least one new capability term is preserved in the fringe list after performing the first search; perform a second search of the data source using the software application names and the capability terms from the taxonomy in electronic hardware memory, after performing the first search, and after updating the taxonomy and updating the fringe list in electronic hardware memory; retrieve a second plurality of text segments from the data source responsive to performing the second search of the data source after updating, wherein each of the text segments of the second plurality includes at least one of the software application names or at least one of the capability terms from the taxonomy in electronic hardware memory; and automatically remove the second new software application name or the second new capability term from the fringe list after updating the fringe list to include the second new software application name or the second new capability term and after performing the second search responsive to a second use frequency for the second new software application name or the second new capability term that is less than the use frequency threshold wherein the second use frequency for the second new software application name or the second new capability term is determined subsequent to performing the second search. | 12. A technology tracking system comprising: a network interface providing coupling over a network; a hardware processor coupled to the network interface; and electronic hardware memory coupled to the hardware processor wherein the electronic hardware memory provides a taxonomy including a plurality of software application names and a plurality of capability terms associated with the software application names, wherein for each of the capability terms, the respective capability term is associated with at least a respective one of the software application names, and wherein the electronic hardware memory comprises computer readable program code that when executed by the hardware processor causes the hardware processor to perform operations to, perform a first search of a data source using the plurality of software application names and the plurality of capability terms from the taxonomy in the electronic hardware memory, wherein the data source is a first data source, retrieve a first plurality of text segments from the data source responsive to performing the first search the data source, wherein each of the text segments includes at least one of the software application names or at least one of the capability terms from the taxonomy in the electronic hardware memory, identify at least one new software application name or at least one new capability term from the first plurality of text segments retrieved from the data source responsive to performing the first search, determine a respective use frequency for each of the at least one new software application name or for each of the at least one new capability term, wherein determining the respective use frequency for each of the at least one new software application name or for each of the at least one new capability term comprises searching a second data source for a number of instances of each of the at least one new software application name of for each of the at least one new capability term, and wherein the second data source is different than the first data source, update the taxonomy in the electronic hardware memory to include at least a first one of the at least one new software application name having the respective use frequency that is greater than the use frequency threshold or to include a first one of the at least one new capability term having the respective use frequency that is greater than the use frequency threshold; update a fringe list in the electronic hardware memory to include a second one of the at least one new software application name having a respective first use frequency that is less than the use frequency threshold or to include a second one of the at least one new capability term having a respective first use frequency that is less than the use frequency threshold, wherein the second one of the at least one new software application name or the second one of the at least one new capability term is preserved in the fringe list after performing the first search; perform a second search of the data source using the software application names and the capability terms from the taxonomy in electronic hardware memory, after performing the first search, and after updating the taxonomy and updating the fringe list in electronic hardware memory; retrieve a second plurality of text segments from the data source responsive to performing the second search of the data source after updating, wherein each of the text segments of the second plurality includes at least one of the software application names or at least one of the capability terms from the taxonomy in electronic hardware memory; and automatically remove the second new software application name or the second new capability term from the fringe list after updating the fringe list to include the second new software application name or the second new capability term and after performing the second search responsive to a second use frequency for the second new software application name or the second new capability term that is less than the use frequency threshold wherein the second use frequency for the second new software application name or the second new capability term is determined subsequent to performing the second search. 18. The technology tracking system of claim 12 wherein at least one of the capability terms is associated with each of the software application names. | 0.962834 |
9,253,224 | 1 | 6 | 1. A non-transitory machine-readable medium carrying one or more sequences of instructions causing a computer to implement a method comprising: providing, to a user by a database service, tools for creating a community website including one or more community webpages to be made accessible to potential subscribers to the community website; receiving, at the database service from the user via the tools, information to configure the community website, the information including one or more potential subscribers to be invited to the community website; in response to receiving the information, sending, by the database service, an invitation to join the community website to each of the potential subscribers; in response to an acceptance of a corresponding invitation by a potential subscriber, creating, by the database service, an active subscriber account on the community website to enable access to the community website, wherein the access to the community website includes allowing the active subscriber account to: post content to the community website, comment on content posted to the community website, participate in discussions on the community website, search for keywords, members, and comments on the community website, send information related to the community website from the community website in an e-mail, and vote on each particular content posted to the community website via selection of a link associated with the particular content, wherein the visually represents a count of a total number of votes cast for the particular content; storing, by the database service for each active subscriber, at least one setting indicating a type of activity occurring on the community website that is of interest to the active subscriber; providing, by the database service to each of the active subscribers, alerts that are responsive to an activity occurring on the community website that is of a type indicated by the at least one setting; generating, by the database service, statistics on the community website that include a count of a number of the active subscribers to the community website; providing, to the user by the database service, tools for the user to create a friend webpage specific to friends of the user; receiving, at the database service from the user via the tools, information to configure a friend webpage specific to another user including information about the other user; configuring, by the database service on behalf of the user, the friend webpage specific to the other user, wherein the friend webpage is configured to include the information about the other user received from the user; and making, by the database service, the friend webpage having the information about the other user accessible only to the user and to additional users given permission by the user. | 1. A non-transitory machine-readable medium carrying one or more sequences of instructions causing a computer to implement a method comprising: providing, to a user by a database service, tools for creating a community website including one or more community webpages to be made accessible to potential subscribers to the community website; receiving, at the database service from the user via the tools, information to configure the community website, the information including one or more potential subscribers to be invited to the community website; in response to receiving the information, sending, by the database service, an invitation to join the community website to each of the potential subscribers; in response to an acceptance of a corresponding invitation by a potential subscriber, creating, by the database service, an active subscriber account on the community website to enable access to the community website, wherein the access to the community website includes allowing the active subscriber account to: post content to the community website, comment on content posted to the community website, participate in discussions on the community website, search for keywords, members, and comments on the community website, send information related to the community website from the community website in an e-mail, and vote on each particular content posted to the community website via selection of a link associated with the particular content, wherein the visually represents a count of a total number of votes cast for the particular content; storing, by the database service for each active subscriber, at least one setting indicating a type of activity occurring on the community website that is of interest to the active subscriber; providing, by the database service to each of the active subscribers, alerts that are responsive to an activity occurring on the community website that is of a type indicated by the at least one setting; generating, by the database service, statistics on the community website that include a count of a number of the active subscribers to the community website; providing, to the user by the database service, tools for the user to create a friend webpage specific to friends of the user; receiving, at the database service from the user via the tools, information to configure a friend webpage specific to another user including information about the other user; configuring, by the database service on behalf of the user, the friend webpage specific to the other user, wherein the friend webpage is configured to include the information about the other user received from the user; and making, by the database service, the friend webpage having the information about the other user accessible only to the user and to additional users given permission by the user. 6. The non-transitory machine-readable medium of claim 1 , wherein the activity includes posting a comment. | 0.91329 |
7,941,749 | 7 | 10 | 7. A system having at least one processor for generating a document containing user-defined properties and document-defined properties, comprising: a text body resolver object operative to receive a document having one or more components, each of the one or more components having document-defined properties according to a document context applied to the document; to receive a text stream containing one or more portions of user-defined information applied to the document; to generate a resolved document object for each of the one or more components of the document, where each resolved document object contains one of the one or more document components and a corresponding one of the one or more portions of user-defined information; and to pass each of the resolved document objects to a text body resolved object for assembly of a text body data structure for the document, wherein the text body resolved object is further operative: to generate a composite text layout document composed of a selected one or more of the resolved document objects assembled into the resolved text body data structure for the document; to receive a selection of one or more of the resolved document objects for application to the composite text layout document; to extract a textual information from each selected one or more resolved document object; to apply a document context associated with the composite text layout document to each extracted textual information from each selected one or more resolved document object; to generate a resolved document object for each extracted textual information after application of the document context associated with the composite text layout; and to pass each of the resolved document objects to the text body resolved object assembly of each extracted textual information into a resolved text body data structure for the composite text layout document. | 7. A system having at least one processor for generating a document containing user-defined properties and document-defined properties, comprising: a text body resolver object operative to receive a document having one or more components, each of the one or more components having document-defined properties according to a document context applied to the document; to receive a text stream containing one or more portions of user-defined information applied to the document; to generate a resolved document object for each of the one or more components of the document, where each resolved document object contains one of the one or more document components and a corresponding one of the one or more portions of user-defined information; and to pass each of the resolved document objects to a text body resolved object for assembly of a text body data structure for the document, wherein the text body resolved object is further operative: to generate a composite text layout document composed of a selected one or more of the resolved document objects assembled into the resolved text body data structure for the document; to receive a selection of one or more of the resolved document objects for application to the composite text layout document; to extract a textual information from each selected one or more resolved document object; to apply a document context associated with the composite text layout document to each extracted textual information from each selected one or more resolved document object; to generate a resolved document object for each extracted textual information after application of the document context associated with the composite text layout; and to pass each of the resolved document objects to the text body resolved object assembly of each extracted textual information into a resolved text body data structure for the composite text layout document. 10. The system of claim 7 , wherein the text body resolver object is further operative to receive each of the one or more portions of user-defined information for applying any document-defined properties of a given document component to a corresponding portion of user-defined information; to parse the document for a document component associated with each of the one or more portions of user-defined information; to extract document-defined properties from an associated document component for a given portion of user-defined information; to apply the document-defined properties extracted from the associated document component to the given portion of user-defined information; and to save the given portion of user-defined information with the applied document-defined properties as a resolved document object for the document component associated with the given portion of user-defined information. | 0.618987 |
4,817,036 | 1 | 19 | 1. In a computer system comprising a CPU, an input/output terminal connected to said CPU, a main CPU memory and a secondary storage means containing a data base, a method of indexing individual records of said data base, and rapidly searching and retrieving selected records corresponding to one or more keywords input to said CPU, said method comprising the steps of: said CPU forming a vector for each said keyword, each said vector comprising one or more array elements which together comprise a numerically sorted list of all record numbers where the keyword for that vector is found; said CPU transforming each said vector so as to form a data base index comprising a bit string for each said vector, said step of transforming each said vector comprising the steps of: (a) transforming said numerically sorted list of record numbers into a binary matrix wherein each row of said matrix corresponds to a binary representation of one of said vector array elements, and wherein each column of said matrix corresponds to a level of said hierarchal tree; (b) determining the first column of said matrix where both ones and zeros are present; (c) grouping said ones and zeros to identify the number of bits in each such group; (d) determining whether the first and last bit in each said group are both ones, are zero and one or both zeros, and outputting a "01," "11" or "10," respectively, so as to form one bit pair of said bit string; (e) splitting the next column of said matrix into groups of bits based on the number of bits in each group determined in step (c); (f) repeating steps (c) and (d) for each said group of said next column; and (g) repeating steps (b) through (f) until each column of said matrix has been done. said CPU storing said data base index in said secondary storage means; inputting at said input/output terminal at least one keyword; said CPU searching said data base index and retrieving the bit string for said keyword input at said terminal; said CPU transforming said retrieving bit string back into the vector for said input keyword; and said CPU identifying at said input/output terminal the records of said data base identified by said list of record numbers associated with the vector for said input keyword. | 1. In a computer system comprising a CPU, an input/output terminal connected to said CPU, a main CPU memory and a secondary storage means containing a data base, a method of indexing individual records of said data base, and rapidly searching and retrieving selected records corresponding to one or more keywords input to said CPU, said method comprising the steps of: said CPU forming a vector for each said keyword, each said vector comprising one or more array elements which together comprise a numerically sorted list of all record numbers where the keyword for that vector is found; said CPU transforming each said vector so as to form a data base index comprising a bit string for each said vector, said step of transforming each said vector comprising the steps of: (a) transforming said numerically sorted list of record numbers into a binary matrix wherein each row of said matrix corresponds to a binary representation of one of said vector array elements, and wherein each column of said matrix corresponds to a level of said hierarchal tree; (b) determining the first column of said matrix where both ones and zeros are present; (c) grouping said ones and zeros to identify the number of bits in each such group; (d) determining whether the first and last bit in each said group are both ones, are zero and one or both zeros, and outputting a "01," "11" or "10," respectively, so as to form one bit pair of said bit string; (e) splitting the next column of said matrix into groups of bits based on the number of bits in each group determined in step (c); (f) repeating steps (c) and (d) for each said group of said next column; and (g) repeating steps (b) through (f) until each column of said matrix has been done. said CPU storing said data base index in said secondary storage means; inputting at said input/output terminal at least one keyword; said CPU searching said data base index and retrieving the bit string for said keyword input at said terminal; said CPU transforming said retrieving bit string back into the vector for said input keyword; and said CPU identifying at said input/output terminal the records of said data base identified by said list of record numbers associated with the vector for said input keyword. 19. A method as defined in claim 1 further comprising the steps of: adding one or more new records to said data base and identifying all keywords contained by said new records; said CPU forming a vector for each keyword of said new records and transforming each vector into a bit string for each keyword of the new records; said CPU searching said data base index and retrieving from said index each keyword corresponding to a keyword contained in said new records, and then merging the bit strings for said corresponding keywords to form an updated bit string for that keyword; and said CPU adding to said index the bit string for each keyword of said new records for which no corresponding keyword was found in said index. | 0.614483 |
8,738,744 | 1 | 2 | 1. A system, comprising: a computer; storage on the computer; a rich media file stored in the storage on the computer; a receiver to receive a request from a user for the rich media file; a user profile for said user stored in the storage on the computer, the user profile specifying whether said user wants to automatically be sent an update to the rich media file; and an auto-notification module to receive said update to the rich media file and to automatically send said update to the rich media file to said user. | 1. A system, comprising: a computer; storage on the computer; a rich media file stored in the storage on the computer; a receiver to receive a request from a user for the rich media file; a user profile for said user stored in the storage on the computer, the user profile specifying whether said user wants to automatically be sent an update to the rich media file; and an auto-notification module to receive said update to the rich media file and to automatically send said update to the rich media file to said user. 2. A system according to claim 1 , further comprising a transaction log stored in the storage on the computer, the transaction log operative to store information about at least one transaction. | 0.502577 |
9,646,164 | 1 | 15 | 1. A computer-implemented method for real-time evaluation of a reverse query to an attribute-based access control (ABAC) policy (P) comprising functional expressions dependent on attributes, wherein the ABAC policy is evaluable for an access request if the access request assigns a value to at least one of said attributes, wherein an access decision resulting from said evaluation is enforced to control access to one or more resources in a computer network, said method comprising the steps of: i) receiving a reverse query indicating a given access decision (d), which is one of permit access and deny access, and further indicating a subset (R) of two or more access requests to the ABAC policy, wherein the subset (R) is defined by constraints over the set of possible access requests; ii) constructing a partial request (r partial ), from the subset (R) of access requests; iii) reducing the ABAC policy in accordance with the partial request; iv) caching the ABAC policy after said reducing, as a simplified policy (P′) comprising at least one functional expression dependent on an attribute; v) translating the cached simplified policy (P′) and the given decision (d) into a satisfiable logic proposition in Boolean variables (vi, i=1, 2, . . . ), including replacing, by a Boolean variable, any Boolean expression in the policy representing a comparison of an attribute and a fixed value; vi) deriving all variable assignments (cj=[v1=xj1, v2=xj2 , . . . ], j=1, 2, . . . ) satisfying the logic proposition; vii) processing the variable assignments satisfying the logic proposition on the basis of a correlation between each Boolean variable and the comparison which it replaces; and viii) controlling access to the one or more resources in the computer network based on the access decision resulting from the evaluation of the ABAC policy. | 1. A computer-implemented method for real-time evaluation of a reverse query to an attribute-based access control (ABAC) policy (P) comprising functional expressions dependent on attributes, wherein the ABAC policy is evaluable for an access request if the access request assigns a value to at least one of said attributes, wherein an access decision resulting from said evaluation is enforced to control access to one or more resources in a computer network, said method comprising the steps of: i) receiving a reverse query indicating a given access decision (d), which is one of permit access and deny access, and further indicating a subset (R) of two or more access requests to the ABAC policy, wherein the subset (R) is defined by constraints over the set of possible access requests; ii) constructing a partial request (r partial ), from the subset (R) of access requests; iii) reducing the ABAC policy in accordance with the partial request; iv) caching the ABAC policy after said reducing, as a simplified policy (P′) comprising at least one functional expression dependent on an attribute; v) translating the cached simplified policy (P′) and the given decision (d) into a satisfiable logic proposition in Boolean variables (vi, i=1, 2, . . . ), including replacing, by a Boolean variable, any Boolean expression in the policy representing a comparison of an attribute and a fixed value; vi) deriving all variable assignments (cj=[v1=xj1, v2=xj2 , . . . ], j=1, 2, . . . ) satisfying the logic proposition; vii) processing the variable assignments satisfying the logic proposition on the basis of a correlation between each Boolean variable and the comparison which it replaces; and viii) controlling access to the one or more resources in the computer network based on the access decision resulting from the evaluation of the ABAC policy. 15. The method of claim 1 , wherein step iii includes partially evaluating the policy (P) over the partial request. | 0.864387 |
7,921,374 | 12 | 15 | 12. A handheld electronic device comprising: a keyboard having a plurality of keys through which at least one sequence of characters can be input and a termination input through which the at least one sequence of characters can be terminated; a display on which the at least one sequence of characters input is displayed; and a processor comprising means examining the at least one sequence of characters for at least one word at the beginning of the sequence of characters indicative of an interrogatory, and means for adding interrogative punctuation to the sequence of characters on the display when the termination input is actuated and the at least one word at the beginning of the at least one sequence of characters is indicative of an interrogatory. | 12. A handheld electronic device comprising: a keyboard having a plurality of keys through which at least one sequence of characters can be input and a termination input through which the at least one sequence of characters can be terminated; a display on which the at least one sequence of characters input is displayed; and a processor comprising means examining the at least one sequence of characters for at least one word at the beginning of the sequence of characters indicative of an interrogatory, and means for adding interrogative punctuation to the sequence of characters on the display when the termination input is actuated and the at least one word at the beginning of the at least one sequence of characters is indicative of an interrogatory. 15. The device of claim 12 , wherein the means having the interrogative punctuation adds a “?” (question mark) at the end of the at least one sequence of characters. | 0.842857 |
5,548,755 | 2 | 7 | 2. The method of claim 1, wherein the query box representation includes a child box of the current box, the child box itself having at least one child referred to as at least one grandchild box, wherein the magic decorrelation process comprises the steps of: performing a feed process to provide the different source for the correlation bindings; determining whether the child box is AMQ or NMQ type; and decorrelating the correlated descendant box by performing steps comprising: if the child box is AMQ type, performing an AMQ absorb process to decorrelate the correlated descendant box using the correlation bindings obtained from the different source, and then performing the feed process to the at least one grandchild box; and if the child box is NMQ type, performing the feed process to the at least one grandchild box to provide the different source of the correlation bindings, and then performing an NMQ absorb process to decorrelate the correlated descendant box using correlation bindings from the different source. | 2. The method of claim 1, wherein the query box representation includes a child box of the current box, the child box itself having at least one child referred to as at least one grandchild box, wherein the magic decorrelation process comprises the steps of: performing a feed process to provide the different source for the correlation bindings; determining whether the child box is AMQ or NMQ type; and decorrelating the correlated descendant box by performing steps comprising: if the child box is AMQ type, performing an AMQ absorb process to decorrelate the correlated descendant box using the correlation bindings obtained from the different source, and then performing the feed process to the at least one grandchild box; and if the child box is NMQ type, performing the feed process to the at least one grandchild box to provide the different source of the correlation bindings, and then performing an NMQ absorb process to decorrelate the correlated descendant box using correlation bindings from the different source. 7. The method of claim 2, wherein the child box has a parent box that comprises a decorrelation output box, said decorrelation output box having a parent box that comprises a correlation input box, said decorrelation output box including a first quantifier ranging over a magic child box associated with the child box, wherein the magic child box comprises a source of the correlation bindings, and wherein the AMQ absorb process comprises the steps of: routing the correlation bindings from the magic child box to the child box and creating an output column in the child box to provide an output of the correlation bindings; substituting the first quantifier in place of the decorrelation output box as the source of the correlated descendant box's correlation bindings; and deleting natural join predicates from the decorrelation output box and the first quantifier. | 0.796912 |
8,978,989 | 1 | 3 | 1. A method of generating a readable matrix code image encoding a message based on an input image and a readable matrix coding specification: calculating function areas readable to comply with a function patterns specification; determining an extent of free cells and derived cells according to a code word specification; calculating decode input values for free cells such that the appearance of the free cells compared to respective areas of the input image complies with a visual perceptual similarity criterion and with the code word specification; and calculating decode input values for derived cells based on the free cells decode input values and in compliance with the code word specification. | 1. A method of generating a readable matrix code image encoding a message based on an input image and a readable matrix coding specification: calculating function areas readable to comply with a function patterns specification; determining an extent of free cells and derived cells according to a code word specification; calculating decode input values for free cells such that the appearance of the free cells compared to respective areas of the input image complies with a visual perceptual similarity criterion and with the code word specification; and calculating decode input values for derived cells based on the free cells decode input values and in compliance with the code word specification. 3. The method according to claim 1 , further comprising: scanning and decoding the readable matrix code to obtain the message. | 0.922509 |
7,543,286 | 1 | 9 | 1. A method for mapping a tag in a markup language (ML) document to a class using namespaces, comprising: analyzing a tag in the ML document; referencing a definition file location attribute in the ML document, wherein the definition file location attribute is identified by the tag; retrieving a definition file from a storage location identified by the definition file location attribute, wherein the definition file includes: a schema that limits the scope of attributes in the definition file, a list of assemblies that references the definition file, a list of common language runtime namespaces associated with the list of assemblies that references the definition file, wherein each common language runtime namespace includes a list of common language classes associated with the common language runtime namespace, and an installation tag that includes a uniform resource identifier for installing assemblies of the list of assemblies; referencing a common language runtime namespace related to the tag within the definition file to determine the common language runtime class associated with the tag; and locating the common language runtime class in an assembly such that the tag is mapped to the common language runtime class. | 1. A method for mapping a tag in a markup language (ML) document to a class using namespaces, comprising: analyzing a tag in the ML document; referencing a definition file location attribute in the ML document, wherein the definition file location attribute is identified by the tag; retrieving a definition file from a storage location identified by the definition file location attribute, wherein the definition file includes: a schema that limits the scope of attributes in the definition file, a list of assemblies that references the definition file, a list of common language runtime namespaces associated with the list of assemblies that references the definition file, wherein each common language runtime namespace includes a list of common language classes associated with the common language runtime namespace, and an installation tag that includes a uniform resource identifier for installing assemblies of the list of assemblies; referencing a common language runtime namespace related to the tag within the definition file to determine the common language runtime class associated with the tag; and locating the common language runtime class in an assembly such that the tag is mapped to the common language runtime class. 9. The method of claim 1 , further comprising generating the ML document, the ML document comprising the tag and the definition file location attribute. | 0.879365 |
7,792,667 | 21 | 32 | 21. A tangible computer readable storage medium containing executable instructions which, if executed in a processing system, cause the system to perform a method for identifying a significant phrase in a document, the method comprising: reading a sequence of words from the document; determining a score for each word in the sequence based on the length of each word; comparing the score for each word in the sequence against a threshold score; indicating that the sequence of words is a significant phrase if the number of words in the sequence that have the score greater than the threshold score equals or exceeds a predetermined number and the number of words in the sequence satisfies the verbosity setting; retrieving a sentence from the document, the sentence containing the sequence of words, if the sequence of words is a significant phrase; and searching an abstract of the document to determine whether the sentence is included in the abstract. | 21. A tangible computer readable storage medium containing executable instructions which, if executed in a processing system, cause the system to perform a method for identifying a significant phrase in a document, the method comprising: reading a sequence of words from the document; determining a score for each word in the sequence based on the length of each word; comparing the score for each word in the sequence against a threshold score; indicating that the sequence of words is a significant phrase if the number of words in the sequence that have the score greater than the threshold score equals or exceeds a predetermined number and the number of words in the sequence satisfies the verbosity setting; retrieving a sentence from the document, the sentence containing the sequence of words, if the sequence of words is a significant phrase; and searching an abstract of the document to determine whether the sentence is included in the abstract. 32. The tangible computer readable storage medium according to claim 21 , wherein the abstract is language independent. | 0.901653 |
8,566,360 | 1 | 2 | 1. A computer-implemented method for automatically generating systematic reviews of documents in a field of literature, comprising a programmed processor performing the following steps: constructing associative networks of documents within the received documents; decomposing the associative networks into clusters of fields or topics; performing part-of-speech tagging of text within the received documents; constructing semantic and ontological structures and/or assertions extracted from the documents; generating citation-based and content-based summaries of the clusters of topics or fields and the semantic and ontological structures; and generating structured narratives of the clusters of field or topic-characterizing documents and the summaries of the generated semantic structures, wherein constructing associative networks of documents within the received documents comprises the processor selecting node types and link types for each time slice of the received documents, computing similarity or proximity scores for the nodes, constructing networks of the node information, and merging respective networks from different time slices. | 1. A computer-implemented method for automatically generating systematic reviews of documents in a field of literature, comprising a programmed processor performing the following steps: constructing associative networks of documents within the received documents; decomposing the associative networks into clusters of fields or topics; performing part-of-speech tagging of text within the received documents; constructing semantic and ontological structures and/or assertions extracted from the documents; generating citation-based and content-based summaries of the clusters of topics or fields and the semantic and ontological structures; and generating structured narratives of the clusters of field or topic-characterizing documents and the summaries of the generated semantic structures, wherein constructing associative networks of documents within the received documents comprises the processor selecting node types and link types for each time slice of the received documents, computing similarity or proximity scores for the nodes, constructing networks of the node information, and merging respective networks from different time slices. 2. The method of claim 1 , further comprising the programmed processor performing the step of merging narratives of the citation-based and content-based summaries into a systematic review having a predetermined arrangement. | 0.825509 |
8,055,669 | 27 | 39 | 27. A server device comprising: a memory to store instructions; and a processor to execute the instructions to: determine one or more alternative terms for one or more terms in the search query; obtain search results based on the search query and based on an indexed corpus of documents, each search result identifying one or more documents in the indexed corpus of documents; define a query context as a plurality of the documents identified by the search results; compare the query context to the alternative terms to generate one or more valid ones of the alternative terms; and incorporate one or more of the valid ones of the alternative terms into the search query to obtain a modified search query. | 27. A server device comprising: a memory to store instructions; and a processor to execute the instructions to: determine one or more alternative terms for one or more terms in the search query; obtain search results based on the search query and based on an indexed corpus of documents, each search result identifying one or more documents in the indexed corpus of documents; define a query context as a plurality of the documents identified by the search results; compare the query context to the alternative terms to generate one or more valid ones of the alternative terms; and incorporate one or more of the valid ones of the alternative terms into the search query to obtain a modified search query. 39. The server device of claim 27 , where the query context includes information relating to phrases and/or pairs of words that occur within predetermined distances of one another in the plurality of documents. | 0.801887 |
9,971,831 | 7 | 10 | 7. A system, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: detect a first query directed towards a dataset which satisfies a size criterion, wherein the first query includes a set of initial predicates and results in a first result set; identify one or more new predicates from the result set, wherein the one or more new predicates are not within the set of initial predicates; detect a second query directed towards the dataset, wherein the second query corresponds with the first query; determine that predicates of the one or more new predicates filter a threshold amount of tuples of an initial set of tuples; determine an order of the one or more new predicates such that a new predicate which filters relatively more tuples of the initial set of tuples is before a new predicate which filters relatively less tuples of the initial set of tuples; and utilize the one or more new predicates to process the second query in the order and determine a second result set for the second query. | 7. A system, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: detect a first query directed towards a dataset which satisfies a size criterion, wherein the first query includes a set of initial predicates and results in a first result set; identify one or more new predicates from the result set, wherein the one or more new predicates are not within the set of initial predicates; detect a second query directed towards the dataset, wherein the second query corresponds with the first query; determine that predicates of the one or more new predicates filter a threshold amount of tuples of an initial set of tuples; determine an order of the one or more new predicates such that a new predicate which filters relatively more tuples of the initial set of tuples is before a new predicate which filters relatively less tuples of the initial set of tuples; and utilize the one or more new predicates to process the second query in the order and determine a second result set for the second query. 10. The system of claim 7 , wherein the first query is identical to the second query. | 0.91966 |
8,032,418 | 11 | 17 | 11. A method of identifying commercial suppliers in response to a keyword, the method being performed by a computerized apparatus linked to a communication network, the method comprising: receiving a keyword from a location along the communication network; searching an index of keywords to identify the keyword and any textual items associated therewith; linking each of a plurality of displayable graphical images, which are stored in the computerized apparatus, wherein each of the displayable graphical images identifies or is associated with a commercial supplier and each of the displayable graphical images is provided to the computerized apparatus independent of any textual items being identified, to a respective one of the textual items, so as to form stored results entries, each stored results entry being arranged to present the textual item and a displayable graphical image linked to the textual item, for simultaneous display; and producing a displayable output list of the stored results entries including the textual items that were identified from the search of the index of keywords and the displayable graphical images linked thereto, such that when the displayable output list is displayed on a computer associated with a user, the computer linked to the communication network, the user is enabled to readily identify a desired commercial supplier from the displayable graphical images in the displayed displayable output list. | 11. A method of identifying commercial suppliers in response to a keyword, the method being performed by a computerized apparatus linked to a communication network, the method comprising: receiving a keyword from a location along the communication network; searching an index of keywords to identify the keyword and any textual items associated therewith; linking each of a plurality of displayable graphical images, which are stored in the computerized apparatus, wherein each of the displayable graphical images identifies or is associated with a commercial supplier and each of the displayable graphical images is provided to the computerized apparatus independent of any textual items being identified, to a respective one of the textual items, so as to form stored results entries, each stored results entry being arranged to present the textual item and a displayable graphical image linked to the textual item, for simultaneous display; and producing a displayable output list of the stored results entries including the textual items that were identified from the search of the index of keywords and the displayable graphical images linked thereto, such that when the displayable output list is displayed on a computer associated with a user, the computer linked to the communication network, the user is enabled to readily identify a desired commercial supplier from the displayable graphical images in the displayed displayable output list. 17. The method according to claim 11 , further comprising combining at least one of the displayable graphical images with textual data, the combined at least one displayable graphical image being compatible with equipment of a requesting user. | 0.541509 |
8,756,571 | 10 | 14 | 10. A non-transitory computer readable storage medium having instructions for causing a computer to execute a method, comprising: displaying a first page of an application being developed that includes an object; receiving a text instruction in a natural language that semantically describes at least two of a location, type, and allowed action of the object on the first page and provides an instruction to execute on the object; executing the instruction on the object to cause the application to display a second page, and testing primitives in the natural language to verify automation steps produce particular results using a natural language test. | 10. A non-transitory computer readable storage medium having instructions for causing a computer to execute a method, comprising: displaying a first page of an application being developed that includes an object; receiving a text instruction in a natural language that semantically describes at least two of a location, type, and allowed action of the object on the first page and provides an instruction to execute on the object; executing the instruction on the object to cause the application to display a second page, and testing primitives in the natural language to verify automation steps produce particular results using a natural language test. 14. The non-transitory computer readable storage medium of claim 10 , wherein the text instruction provides a spatial relationship of the object with respect to another object being displayed on the first page. | 0.740099 |
9,535,982 | 1 | 5 | 1. A product comprising: a non-transitory machine readable memory; an ontology model stored in the memory and defining a hierarchy of document structure instance classes comprising a root class, a child class, and class definition relationships between the document structure instance classes; and logic stored in the memory for execution by a processor, the logic comprising: document structure instance identification logic configured to cause the processor to: identify a first document structure instance and a second document structure instance in a document; classification logic configured to: analyze the first document structure instance against the ontology model to determine a first classification for the first document structure instance among the document structure instance classes; analyze the second document structure instance against the ontology model to determine a second classification for the second document structure instance among the document structure instance classes, wherein a horizontal relationship exists between the first classification and the second classification such that neither of the first and second classifications are ancestors of the other; and instance relationship analysis logic configured to cause the processor to: analyze the class definition relationships to determine whether a change in the first classification affects the second classification, and based on the analysis, output an analysis result that indicates whether the first classification affects the second classification, wherein the analysis result facilitates determining whether conflicts exist between the first and second document structure instances of the document, which in turn facilitates improving an accuracy, completeness, and clarity of the document. | 1. A product comprising: a non-transitory machine readable memory; an ontology model stored in the memory and defining a hierarchy of document structure instance classes comprising a root class, a child class, and class definition relationships between the document structure instance classes; and logic stored in the memory for execution by a processor, the logic comprising: document structure instance identification logic configured to cause the processor to: identify a first document structure instance and a second document structure instance in a document; classification logic configured to: analyze the first document structure instance against the ontology model to determine a first classification for the first document structure instance among the document structure instance classes; analyze the second document structure instance against the ontology model to determine a second classification for the second document structure instance among the document structure instance classes, wherein a horizontal relationship exists between the first classification and the second classification such that neither of the first and second classifications are ancestors of the other; and instance relationship analysis logic configured to cause the processor to: analyze the class definition relationships to determine whether a change in the first classification affects the second classification, and based on the analysis, output an analysis result that indicates whether the first classification affects the second classification, wherein the analysis result facilitates determining whether conflicts exist between the first and second document structure instances of the document, which in turn facilitates improving an accuracy, completeness, and clarity of the document. 5. The product of claim 1 , wherein the analysis result comprises a relationship notification message inserted into the document. | 0.754753 |
8,635,530 | 1 | 2 | 1. A method of data filtering in an information technology system, comprising: generating a graphical statistical representation of a data set in a first graphical user interface; displaying the graphical statistical representation on an electronic display; displaying multiple manipulable graphical elements in a second graphical user interface in conjunction with the graphical statistical representation, wherein a pair of particular manipulable graphical elements represents statistical ranges for the graphical statistical representation on either side of another particular manipulable graphical element; receiving user input adjusting one or more of the manipulable graphical elements specifying one or more adjusted statistical ranges; filtering the data set to correspond to the graphical statistical representation within the one or more adjusted statistical ranges; wherein, the graphical statistical representation of the data set comprises a bell curve, each of the pair of particular manipulable graphical elements adjust a separate statistical range on different sides of the other particular manipulable graphical element, and the other particular manipulable graphical element adjusts a statistical percentile. | 1. A method of data filtering in an information technology system, comprising: generating a graphical statistical representation of a data set in a first graphical user interface; displaying the graphical statistical representation on an electronic display; displaying multiple manipulable graphical elements in a second graphical user interface in conjunction with the graphical statistical representation, wherein a pair of particular manipulable graphical elements represents statistical ranges for the graphical statistical representation on either side of another particular manipulable graphical element; receiving user input adjusting one or more of the manipulable graphical elements specifying one or more adjusted statistical ranges; filtering the data set to correspond to the graphical statistical representation within the one or more adjusted statistical ranges; wherein, the graphical statistical representation of the data set comprises a bell curve, each of the pair of particular manipulable graphical elements adjust a separate statistical range on different sides of the other particular manipulable graphical element, and the other particular manipulable graphical element adjusts a statistical percentile. 2. The method of claim 1 , further comprising: displaying the data set along with the graphical statistical representation on the electronic display, wherein the second graphical user interface is displayed within the first graphical user interface. | 0.793874 |
7,523,126 | 1 | 19 | 1. A method of displaying data, comprising the steps of: (1) defining a set of documents, each document having a unique identification, the set being defined by selecting at least one starting document, with the set further comprising documents being included based on predetermined relationships to information derived from said at least one starting document; (2) generating a hierarchal tree representation of at least one subset of the set of documents, a subset inclusion and hierarchy thereof being defined by said predetermined relationships between documents within the set; and (3) selectively focusing on a node of said hierarchal tree, to define a graphic display representation of at least a portion thereof to emphasize the selected focus while depicting the hierarchal relationships. | 1. A method of displaying data, comprising the steps of: (1) defining a set of documents, each document having a unique identification, the set being defined by selecting at least one starting document, with the set further comprising documents being included based on predetermined relationships to information derived from said at least one starting document; (2) generating a hierarchal tree representation of at least one subset of the set of documents, a subset inclusion and hierarchy thereof being defined by said predetermined relationships between documents within the set; and (3) selectively focusing on a node of said hierarchal tree, to define a graphic display representation of at least a portion thereof to emphasize the selected focus while depicting the hierarchal relationships. 19. The method according to claim 1 , further comprising the step of emphasizing documents of said hierarchal tree according to a time-based criteria associated with a document. | 0.664773 |
6,016,499 | 56 | 61 | 56. A system providing access to a directory services repository which is stored on a computer system, the claimed system comprising: a directory services application programming interface, also known as the API, which includes at least one callable element that is capable of accessing a component of the directory services repository in response to being called; and a driver which is capable of translating a relational database language statement into an executable API sequence that includes a call to the callable element and produces an API result, the driver also being capable of translating the API result into a relational database result, wherein the directory services repository component includes an attribute which has a plurality of simultaneous values, the relational database language statement identifies a column of a table, the driver and the API together map the attribute to the column, and the driver and the API together map each value of the attribute to a separate row in the table, thereby presenting a one-to-many relation. | 56. A system providing access to a directory services repository which is stored on a computer system, the claimed system comprising: a directory services application programming interface, also known as the API, which includes at least one callable element that is capable of accessing a component of the directory services repository in response to being called; and a driver which is capable of translating a relational database language statement into an executable API sequence that includes a call to the callable element and produces an API result, the driver also being capable of translating the API result into a relational database result, wherein the directory services repository component includes an attribute which has a plurality of simultaneous values, the relational database language statement identifies a column of a table, the driver and the API together map the attribute to the column, and the driver and the API together map each value of the attribute to a separate row in the table, thereby presenting a one-to-many relation. 61. The system of claim 56, wherein the relational database language statement conforms with at least one version of the Open Database Connectivity standard. | 0.805211 |
10,133,755 | 18 | 23 | 18. A method for applying legal analytics, the method comprising: accessing a source of legal information; retrieving legal data from the source of legal information; performing word recognition on the legal data; automatically normalizing inaccuracies discovered in the legal data; after normalizing the legal data, receiving input from an administrator to input supplemental legal data that adds a legal outcome for which no metadata element has been previously generated and modify the legal data; identifying, based on any recognized words, references to various legal entities in the legal data; identifying portions of the legal data that include at least one reference; associating each of the portions with a metadata element corresponding to the at least one legal entity referenced in each portion; and constructing a database that includes the legal data and metadata elements, wherein the database is searchable by legal entity; allowing a user to specify search parameters that are used to identify a segment of the legal data; applying legal analytics to the segment of the legal data; and presenting analytic results to the user. | 18. A method for applying legal analytics, the method comprising: accessing a source of legal information; retrieving legal data from the source of legal information; performing word recognition on the legal data; automatically normalizing inaccuracies discovered in the legal data; after normalizing the legal data, receiving input from an administrator to input supplemental legal data that adds a legal outcome for which no metadata element has been previously generated and modify the legal data; identifying, based on any recognized words, references to various legal entities in the legal data; identifying portions of the legal data that include at least one reference; associating each of the portions with a metadata element corresponding to the at least one legal entity referenced in each portion; and constructing a database that includes the legal data and metadata elements, wherein the database is searchable by legal entity; allowing a user to specify search parameters that are used to identify a segment of the legal data; applying legal analytics to the segment of the legal data; and presenting analytic results to the user. 23. The method of claim 18 , wherein the legal data includes case information, docket information, electronic documents, or any combination thereof. | 0.843882 |
8,095,575 | 1 | 8 | 1. A computer-implemented word processing presentation method, comprising: obtaining an unformatted data structure containing a series of characters representing content for a word processing document; accessing a series of first records in a data structure associated with the unformatted data structure file, wherein each first record contains data correlating a location of one or more characters in the unformatted data structure to a location for the one or more characters in the word processing document; generating a display of the word processing document by applying the correlating data from the series of records to the series of characters in the unformatted data structure; receiving a command to delete particular characters from the word processing document, wherein the particular characters are included in the unformatted data structure; and in response to receiving the command to delete characters, generating a record in the series of records that indicates that the particular characters are deleted from the word processing document while leaving the particular characters in the unformatted data structure unchanged. | 1. A computer-implemented word processing presentation method, comprising: obtaining an unformatted data structure containing a series of characters representing content for a word processing document; accessing a series of first records in a data structure associated with the unformatted data structure file, wherein each first record contains data correlating a location of one or more characters in the unformatted data structure to a location for the one or more characters in the word processing document; generating a display of the word processing document by applying the correlating data from the series of records to the series of characters in the unformatted data structure; receiving a command to delete particular characters from the word processing document, wherein the particular characters are included in the unformatted data structure; and in response to receiving the command to delete characters, generating a record in the series of records that indicates that the particular characters are deleted from the word processing document while leaving the particular characters in the unformatted data structure unchanged. 8. The method of claim 1 , further comprising accessing a series of second records in a data structure associated with the unformatted data structure, and wherein each second record contains data correlating one or more characters in the unformatted data structure to a paragraph format for the one or more characters in the word processing document. | 0.633124 |
8,650,094 | 1 | 11 | 1. A method, implemented at least in part by a computing device, comprising: defining a vocabulary for emotions; extracting descriptions for one or more songs from web-based information that describes the one or more songs; generating one or more first distributions for the one or more songs in an emotion space based at least in part on the vocabulary and the extracted descriptions; extracting one or more salient words from a document; generating a second distribution for the document in the emotion space based at least in part on the vocabulary and the extracted salient words; and at the computing device, comparing the second distribution for the document to at least one of the first distributions for the one or more songs to provide at least one song recommendation corresponding to the second distribution for the document in the emotion space. | 1. A method, implemented at least in part by a computing device, comprising: defining a vocabulary for emotions; extracting descriptions for one or more songs from web-based information that describes the one or more songs; generating one or more first distributions for the one or more songs in an emotion space based at least in part on the vocabulary and the extracted descriptions; extracting one or more salient words from a document; generating a second distribution for the document in the emotion space based at least in part on the vocabulary and the extracted salient words; and at the computing device, comparing the second distribution for the document to at least one of the first distributions for the one or more songs to provide at least one song recommendation corresponding to the second distribution for the document in the emotion space. 11. The method of claim 1 wherein the document comprises a web document. | 0.804348 |
9,129,031 | 1 | 8 | 1. A method of automatically configuring a portlet, the method comprising: receiving a portlet with content to be rendered as a portlet window object within a portal; examining the content of the portlet for discovering a contextual aspect; and automatically adjusting at least one attribute of the portlet window object based on the discovered contextual aspect. | 1. A method of automatically configuring a portlet, the method comprising: receiving a portlet with content to be rendered as a portlet window object within a portal; examining the content of the portlet for discovering a contextual aspect; and automatically adjusting at least one attribute of the portlet window object based on the discovered contextual aspect. 8. The method of claim 1 , wherein the applying attribute information includes adjusting an appearance of the portlet to signify a content of the portlet. | 0.646789 |
9,436,882 | 1 | 4 | 1. One or more non-transitory computer-readable media having instructions stored thereon which, when executed by a processor of a computing device, provide the computing device with a redaction module to: receive a request to redact a selection of a group of text from a document, wherein the group of text comprises one or more words; identify instances of the group of text occurring within the document, including for each instance of the group of text, word coordinate information of the one or more words of the instance, wherein the word coordinate information of the one or more words of the instance includes (x, y) coordinates of the one or more words; and generate redaction information for a redaction mask, including redaction coordinates, for each instance of the group of text, wherein the redaction coordinates of each redaction mask include (x, y) coordinates of the redaction mask, wherein generation of the (x, y) coordinates of a redaction mask is based at least in part on the (x, y) coordinates of the one or more words of the instance of the group of text to be redacted, wherein application of the redaction masks in accordance with the redaction coordinates of the redaction masks redacts the respective instances of the group of text, wherein a y-height of the mask is substantially equal to a height of a tallest letter within the respective instances of the group of text, wherein the height of the tallest letter is greater than heights of at least some of other letters within the respective instances of the group of text. | 1. One or more non-transitory computer-readable media having instructions stored thereon which, when executed by a processor of a computing device, provide the computing device with a redaction module to: receive a request to redact a selection of a group of text from a document, wherein the group of text comprises one or more words; identify instances of the group of text occurring within the document, including for each instance of the group of text, word coordinate information of the one or more words of the instance, wherein the word coordinate information of the one or more words of the instance includes (x, y) coordinates of the one or more words; and generate redaction information for a redaction mask, including redaction coordinates, for each instance of the group of text, wherein the redaction coordinates of each redaction mask include (x, y) coordinates of the redaction mask, wherein generation of the (x, y) coordinates of a redaction mask is based at least in part on the (x, y) coordinates of the one or more words of the instance of the group of text to be redacted, wherein application of the redaction masks in accordance with the redaction coordinates of the redaction masks redacts the respective instances of the group of text, wherein a y-height of the mask is substantially equal to a height of a tallest letter within the respective instances of the group of text, wherein the height of the tallest letter is greater than heights of at least some of other letters within the respective instances of the group of text. 4. The one or more non-transitory computer-readable media of claim 1 , wherein the redaction module is to further identify groups of words within the document as instances of the text from the document by computation of respective Levenshtein distance values between the groups of words and the text, and a determination of whether each Levenshtein distance value is within a determined threshold. | 0.699697 |
7,487,446 | 21 | 30 | 21. A computing apparatus, comprising: a display unit that is capable of generating video images; an input device; a processing apparatus operatively coupled to said display unit and said input device, said processing apparatus comprising a processor and a memory operatively coupled to said processor, a network interface connected to a network and to the processing apparatus; said processing apparatus being programmed to select a template in an accounting program wherein the template has a field related to the selected template; said processing apparatus being programmed to identify an open field in the selected template that can be filled in with data from the accounting program; said processing apparatus being programmed to select data stored by the accounting program that is appropriate to fill in the open field in the selected template; said processing apparatus being programmed to communicate the selected data and the selected template to the word processing program; said processing apparatus being programmed to open a document in the word processing program that displays the selected template and the selected data in the appropriate field as a word processing document; and said processing apparatus being programmed to allow the modifications made on the word processing document to be communicated to the accounting program. | 21. A computing apparatus, comprising: a display unit that is capable of generating video images; an input device; a processing apparatus operatively coupled to said display unit and said input device, said processing apparatus comprising a processor and a memory operatively coupled to said processor, a network interface connected to a network and to the processing apparatus; said processing apparatus being programmed to select a template in an accounting program wherein the template has a field related to the selected template; said processing apparatus being programmed to identify an open field in the selected template that can be filled in with data from the accounting program; said processing apparatus being programmed to select data stored by the accounting program that is appropriate to fill in the open field in the selected template; said processing apparatus being programmed to communicate the selected data and the selected template to the word processing program; said processing apparatus being programmed to open a document in the word processing program that displays the selected template and the selected data in the appropriate field as a word processing document; and said processing apparatus being programmed to allow the modifications made on the word processing document to be communicated to the accounting program. 30. The computing apparatus of claim 21 , the processing apparatus being programmed to print using the word processing program in such that the word processing program operates internally and is not visible to the user. | 0.627551 |
9,213,885 | 1 | 6 | 1. A computer-implemented method of face recognition in digitized images, comprising: applying a view-based classifier to a pair of digitized images, wherein the classifier includes a plurality of sub-classifiers; computing a sum of log-likelihood ratios for each of the plurality of sub-classifiers, each of the log-likelihood ratios including a ratio of a first graphical probability model representing a probability distribution over image pairs that come from the same person and a second graphical probability model representing a probability distribution over image pairs that come from different people, wherein each of the first and second graphical probability models includes a probability distribution over a set of variables where statistical independence and conditional statistical independence exist among various combinations of the variables, and wherein the graphical probability model is a probability distribution representation derived from statistical dependencies among image input variables; and determining whether the pair of digitized images are images of the same person based on the sum of log-likelihood ratios. | 1. A computer-implemented method of face recognition in digitized images, comprising: applying a view-based classifier to a pair of digitized images, wherein the classifier includes a plurality of sub-classifiers; computing a sum of log-likelihood ratios for each of the plurality of sub-classifiers, each of the log-likelihood ratios including a ratio of a first graphical probability model representing a probability distribution over image pairs that come from the same person and a second graphical probability model representing a probability distribution over image pairs that come from different people, wherein each of the first and second graphical probability models includes a probability distribution over a set of variables where statistical independence and conditional statistical independence exist among various combinations of the variables, and wherein the graphical probability model is a probability distribution representation derived from statistical dependencies among image input variables; and determining whether the pair of digitized images are images of the same person based on the sum of log-likelihood ratios. 6. The method of claim 1 , further comprising: sequentially comparing each of said sum of log-likelihood ratios to a predetermined threshold. | 0.842984 |
9,892,110 | 9 | 14 | 9. A system comprising: a corpus module configured to receive text from a plurality of documents; a text selection module configured to, for each document of the plurality of documents, segment the received text of the particular document of the plurality of documents to create a set of segments, each segment including two or more words; for each of at least a subset of the segments of the set of segments: calculate a document frequency statistic indicating a frequency of a particular segment of the at least a subset of the segments within the particular document of the plurality of documents, compare the document frequency statistic indicating the frequency of the particular segment within the particular document to a frequency threshold, and determine if the particular segment is a segment of potential interest of the at least the subset of the segments of the set of segments based on the comparison of the document frequency statistic of the particular segment indicating the frequency of the particular segment within the particular document to the frequency threshold; a distance module configured to calculate a distance between the particular document of the plurality of documents and each of the other documents of the plurality of documents using a text metric; a search database configured to store the received text, the segments of potential interest of each document, the distances, and the document frequency statistics; a search module configured to receive a search query and perform a search on the received text of the plurality of documents to generate search results, the search results including at least a subset of documents of the plurality of documents; a partition module configured to: divide the at least the subset of the documents of the plurality of documents of the search results between a first set and a guide set, for each of the documents of the first set, determine a closest document of the guide set using the distances for that particular document to create partitions of documents, and for each partition of documents: retrieve the document frequency statistics of each segment of potential interest of each document in the particular partition of documents, and select a predetermined number of segments of potential interest of the documents in the particular partition of documents based on a highest frequency statistic of the retrieved document frequency statistics; and a label module configured to: for each partition, determine a label for that particular partition of documents including at least one of the predetermined number of segments of potential interest of the documents in that particular partition of documents, and provide the labels for each partition for display. | 9. A system comprising: a corpus module configured to receive text from a plurality of documents; a text selection module configured to, for each document of the plurality of documents, segment the received text of the particular document of the plurality of documents to create a set of segments, each segment including two or more words; for each of at least a subset of the segments of the set of segments: calculate a document frequency statistic indicating a frequency of a particular segment of the at least a subset of the segments within the particular document of the plurality of documents, compare the document frequency statistic indicating the frequency of the particular segment within the particular document to a frequency threshold, and determine if the particular segment is a segment of potential interest of the at least the subset of the segments of the set of segments based on the comparison of the document frequency statistic of the particular segment indicating the frequency of the particular segment within the particular document to the frequency threshold; a distance module configured to calculate a distance between the particular document of the plurality of documents and each of the other documents of the plurality of documents using a text metric; a search database configured to store the received text, the segments of potential interest of each document, the distances, and the document frequency statistics; a search module configured to receive a search query and perform a search on the received text of the plurality of documents to generate search results, the search results including at least a subset of documents of the plurality of documents; a partition module configured to: divide the at least the subset of the documents of the plurality of documents of the search results between a first set and a guide set, for each of the documents of the first set, determine a closest document of the guide set using the distances for that particular document to create partitions of documents, and for each partition of documents: retrieve the document frequency statistics of each segment of potential interest of each document in the particular partition of documents, and select a predetermined number of segments of potential interest of the documents in the particular partition of documents based on a highest frequency statistic of the retrieved document frequency statistics; and a label module configured to: for each partition, determine a label for that particular partition of documents including at least one of the predetermined number of segments of potential interest of the documents in that particular partition of documents, and provide the labels for each partition for display. 14. The system of claim 9 wherein the distance is a result of applying a cosine term frequency-inverse document frequency (tf-idf). | 0.897174 |
7,529,666 | 1 | 2 | 1. A method of providing pattern recognition, said method comprising the steps of: inputting a speech pattern into a pattern recognition apparatus; providing minimum Bayes error feature selection via transforming the input pattern to provide a set of features for a classifier which classifies into classes, wherein there is only one feature space transformation for all classes; and providing final features to the classifier, wherein the classifier provides a final output classification result; said transforming step comprising the step of directly minimizing the probability of subsequent misclassification in a projected space of at least one feature; said direct minimizing step comprising: performing a full-covariance gaussian clustering of input records for every class; developing an objective function by way of means, covariances and priors, wherein said objective function either: maximizes an average pairwise divergence and relates it to Bayes error; or directly minimizes an upper bound on Bayes error; optimizing the objective function through gradient decent, wherein all dimensions of a matrix are optimized via optimizing the objective function; wherein the optimizing is carried out over all possible matrices; and wherein the objective function is initialized with an LDA matrix (linear discriminant analysis); upon convergence of the optimization, transforming all the records x into y=θx to produce the at least one final feature where 0 is the LDA matrix; wherein said pattern recognition is speech recognition. | 1. A method of providing pattern recognition, said method comprising the steps of: inputting a speech pattern into a pattern recognition apparatus; providing minimum Bayes error feature selection via transforming the input pattern to provide a set of features for a classifier which classifies into classes, wherein there is only one feature space transformation for all classes; and providing final features to the classifier, wherein the classifier provides a final output classification result; said transforming step comprising the step of directly minimizing the probability of subsequent misclassification in a projected space of at least one feature; said direct minimizing step comprising: performing a full-covariance gaussian clustering of input records for every class; developing an objective function by way of means, covariances and priors, wherein said objective function either: maximizes an average pairwise divergence and relates it to Bayes error; or directly minimizes an upper bound on Bayes error; optimizing the objective function through gradient decent, wherein all dimensions of a matrix are optimized via optimizing the objective function; wherein the optimizing is carried out over all possible matrices; and wherein the objective function is initialized with an LDA matrix (linear discriminant analysis); upon convergence of the optimization, transforming all the records x into y=θx to produce the at least one final feature where 0 is the LDA matrix; wherein said pattern recognition is speech recognition. 2. The method of claim 1 , further comprising the step of querying whether the optimized objective function converges. | 0.78777 |
9,606,897 | 1 | 3 | 1. A method for automated semantic parsing of an image of a structured document, the method comprising: acquiring the image of the structured document by an image acquiring device; lexing the image of the structured document so as to associate each image element of a plurality of image elements of the image with a predefined token; wherein lexing the image comprises associating an element of the image with a plurality of possible tokens, each association with a possible token being assigned a likelihood value; inputting a user defined template of expected semantically significant elements of the structured document into a parser, the expected elements being defined in a visibly pushdown language (VPL) format; and parsing one or more of the tokens into an element of the expected elements. | 1. A method for automated semantic parsing of an image of a structured document, the method comprising: acquiring the image of the structured document by an image acquiring device; lexing the image of the structured document so as to associate each image element of a plurality of image elements of the image with a predefined token; wherein lexing the image comprises associating an element of the image with a plurality of possible tokens, each association with a possible token being assigned a likelihood value; inputting a user defined template of expected semantically significant elements of the structured document into a parser, the expected elements being defined in a visibly pushdown language (VPL) format; and parsing one or more of the tokens into an element of the expected elements. 3. The method of claim 1 , wherein inputting the template comprises compiling the template by a compiler. | 0.589844 |
8,775,444 | 13 | 15 | 13. A system for generating an aggregate document slice from an existing aggregate document comprising: a computing system including at least one computing device, the computing system configured to: identify at least three data pages in a plurality of data pages included in an existing aggregate document that satisfy node selection criteria, the node selection criteria including a user entered term having a series of characters, identifying the at least three data pages including searching metadata associated with the existing aggregate document using the node selection criteria; create an aggregate document slice to be a second document different from the existing aggregate document, creating the aggregate document slice comprising: inserting into the aggregate document slice a copy of the identified data pages, wherein the pages inserted into the aggregate document slice are a proper subset of the plurality of data pages; import relationships connecting the plurality of data pages included in the existing aggregate document into the aggregate document slice to form at least one continuous path of relationships connecting the data pages inserted into the aggregate document slice, importing the relationships comprising: omitting a relationship between a data page inserted in the aggregate document slice and a data page of the existing aggregate document slice when the data page of the existing aggregate document is not included in the aggregate document slice generating a new relationship connecting at least two of the pages inserted into the aggregate document slice to establish continuity of the at least one continuous path when the continuity is otherwise lacking; and selecting a start node of the aggregate document slice; generating a second underlying data structure for the aggregate document slice; copying portions of a first underlying data structure for the existing aggregate document, the copied portions corresponding to the data pages to be added to the aggregate document slice; and inserting the copied portions of the first underlying data structure into the second underlying data structure. | 13. A system for generating an aggregate document slice from an existing aggregate document comprising: a computing system including at least one computing device, the computing system configured to: identify at least three data pages in a plurality of data pages included in an existing aggregate document that satisfy node selection criteria, the node selection criteria including a user entered term having a series of characters, identifying the at least three data pages including searching metadata associated with the existing aggregate document using the node selection criteria; create an aggregate document slice to be a second document different from the existing aggregate document, creating the aggregate document slice comprising: inserting into the aggregate document slice a copy of the identified data pages, wherein the pages inserted into the aggregate document slice are a proper subset of the plurality of data pages; import relationships connecting the plurality of data pages included in the existing aggregate document into the aggregate document slice to form at least one continuous path of relationships connecting the data pages inserted into the aggregate document slice, importing the relationships comprising: omitting a relationship between a data page inserted in the aggregate document slice and a data page of the existing aggregate document slice when the data page of the existing aggregate document is not included in the aggregate document slice generating a new relationship connecting at least two of the pages inserted into the aggregate document slice to establish continuity of the at least one continuous path when the continuity is otherwise lacking; and selecting a start node of the aggregate document slice; generating a second underlying data structure for the aggregate document slice; copying portions of a first underlying data structure for the existing aggregate document, the copied portions corresponding to the data pages to be added to the aggregate document slice; and inserting the copied portions of the first underlying data structure into the second underlying data structure. 15. The system of claim 13 , wherein the new relationship is generated to connect one of the data pages in the aggregate document slice to another one of the data pages in the aggregate document slice in response to a determination that none of the remaining data pages in the aggregate document slice connect to the one of the data pages. | 0.711735 |
8,825,648 | 1 | 7 | 1. A method comprising: under a control of one or more processors, identifying multiple concept-units from a multi-language document corpus, a respective concept-unit including a set of documents in a plurality of languages describing a particular concept, the identifying including identifying one or more hyperlinks or references within a respective document that identify one or more other documents in one or more other languages relating to the particular concept; and modeling the concept-units of the multi-language document corpus by maintaining a separation of term-by-document matrices for the plurality of languages to create a generative model, the generative model representing: a plurality of universal topics, at least one respective universal topic being defined by a plurality of topic word distributions in the plurality of languages, at least one of the plurality of topic word distributions for a respective universal topic corresponding to a respective language from the plurality of languages and including one or more words in the respective language with corresponding probability values characterizing the respective universal topic; and a topic distribution for at least one concept-unit, the topic distribution for a respective concept-unit including one or more universal topics and their distributions for the respective concept-unit, the set of documents in the different plurality of languages of the respective concept-unit being constrained to share a common topic distribution. | 1. A method comprising: under a control of one or more processors, identifying multiple concept-units from a multi-language document corpus, a respective concept-unit including a set of documents in a plurality of languages describing a particular concept, the identifying including identifying one or more hyperlinks or references within a respective document that identify one or more other documents in one or more other languages relating to the particular concept; and modeling the concept-units of the multi-language document corpus by maintaining a separation of term-by-document matrices for the plurality of languages to create a generative model, the generative model representing: a plurality of universal topics, at least one respective universal topic being defined by a plurality of topic word distributions in the plurality of languages, at least one of the plurality of topic word distributions for a respective universal topic corresponding to a respective language from the plurality of languages and including one or more words in the respective language with corresponding probability values characterizing the respective universal topic; and a topic distribution for at least one concept-unit, the topic distribution for a respective concept-unit including one or more universal topics and their distributions for the respective concept-unit, the set of documents in the different plurality of languages of the respective concept-unit being constrained to share a common topic distribution. 7. A method as recited in claim 1 , further comprising: obtaining topic distributions of documents of a classified document corpus; obtaining topic distributions of documents of an unclassified document corpus; comparing topic distributions between the documents of the unclassified document corpus and the documents of the classified document corpus; and classifying one or more documents of the unclassified document corpus according to classifications of documents in the classified document corpus having common topic distributions with the one or more documents of the unclassified document corpus. | 0.500828 |
8,554,281 | 1 | 5 | 1. A method of automatically establishing an input language for a handheld electronic device that stores contact information for a plurality of contacts, comprising: receiving a request to initiate composition of a new message to a particular one of said contacts and one or more additional ones of said contacts, each of said particular one of said contacts and said one or more additional contacts having a respective preferred input language stored by said handheld electronic device and each of said particular one of said contacts and said one or more additional contacts being intended recipients of said new message; responsive to receiving said request, displaying contact information reflecting said particular one of said contacts and one or more additional ones of said contacts and each respective preferred input language; receiving a selection of a particular preferred input language from among said displayed respective preferred input languages; determining whether said particular preferred input language is different than a default input language of said handheld electronic device; if it is determined that the particular preferred input language is different than the default input language, switching a current input language of said handheld electronic device to said particular preferred input language; and if it is determined that the composition of the new message is complete and the particular preferred input language is different than the default input language, switching the current input language of said handheld electronic device back to the default input language. | 1. A method of automatically establishing an input language for a handheld electronic device that stores contact information for a plurality of contacts, comprising: receiving a request to initiate composition of a new message to a particular one of said contacts and one or more additional ones of said contacts, each of said particular one of said contacts and said one or more additional contacts having a respective preferred input language stored by said handheld electronic device and each of said particular one of said contacts and said one or more additional contacts being intended recipients of said new message; responsive to receiving said request, displaying contact information reflecting said particular one of said contacts and one or more additional ones of said contacts and each respective preferred input language; receiving a selection of a particular preferred input language from among said displayed respective preferred input languages; determining whether said particular preferred input language is different than a default input language of said handheld electronic device; if it is determined that the particular preferred input language is different than the default input language, switching a current input language of said handheld electronic device to said particular preferred input language; and if it is determined that the composition of the new message is complete and the particular preferred input language is different than the default input language, switching the current input language of said handheld electronic device back to the default input language. 5. The method according to claim 1 , wherein said step of receiving a request is performed prior to said step of receiving a selection. | 0.580745 |
9,979,777 | 1 | 5 | 1. A method comprising: determining, using one or more processors, an inferred interest for a first user; generating, using the one or more processors, a model based on the inferred interest of the first user and storing the model in a non-transitory storage medium; generating, using the one or more processors, a set of candidate content items using an item from a second user with a similarity to the first user; determining, using the one or more processors, a first attribute and a second attribute associated with a candidate content item in the set of candidate content items; determining, using the one or more processors, a first score associated with the first attribute for the candidate content item based on the model of the first user and a first number of candidate content items having the first attribute in the set of candidate content items; determining, using the one or more processors, a second score associated with the second attribute for the candidate content item based on the model of the first user and a second number of candidate content items having the second attribute in the set of candidate content items; computing, using the one or more processors, a third score for the candidate content item in the set of candidate content items by summing the first score associated with the first attribute and the second score associated with the second attribute; selecting, using the one or more processors, content items for a stream of content associated with the first user from the set of candidate content items based on the third score of the content items; generating, using the one or more processors, an explanation for a first content item in the selected content items, the explanation indicating a reason for presenting the first content item to the first user; and transmitting, using the one or more processors, an instruction to a device that causes the device to present for display the stream of content to the first user with the explanation alongside the first content item, the explanation including a selectable graphic element for the first user to access an expanded explanation. | 1. A method comprising: determining, using one or more processors, an inferred interest for a first user; generating, using the one or more processors, a model based on the inferred interest of the first user and storing the model in a non-transitory storage medium; generating, using the one or more processors, a set of candidate content items using an item from a second user with a similarity to the first user; determining, using the one or more processors, a first attribute and a second attribute associated with a candidate content item in the set of candidate content items; determining, using the one or more processors, a first score associated with the first attribute for the candidate content item based on the model of the first user and a first number of candidate content items having the first attribute in the set of candidate content items; determining, using the one or more processors, a second score associated with the second attribute for the candidate content item based on the model of the first user and a second number of candidate content items having the second attribute in the set of candidate content items; computing, using the one or more processors, a third score for the candidate content item in the set of candidate content items by summing the first score associated with the first attribute and the second score associated with the second attribute; selecting, using the one or more processors, content items for a stream of content associated with the first user from the set of candidate content items based on the third score of the content items; generating, using the one or more processors, an explanation for a first content item in the selected content items, the explanation indicating a reason for presenting the first content item to the first user; and transmitting, using the one or more processors, an instruction to a device that causes the device to present for display the stream of content to the first user with the explanation alongside the first content item, the explanation including a selectable graphic element for the first user to access an expanded explanation. 5. The method of claim 1 , wherein selecting the content items for the stream of content includes selecting candidate content items that have the third score exceeding a threshold score. | 0.778043 |
8,510,257 | 3 | 4 | 3. The non-transitory storage medium as set forth in claim 2 , wherein the performing LDA comprises: performing LDA with an IBP compound Dirichlet prior probability distribution configured such that the inferred topic model associates a focused sub-set of the set of topics to each document of the training corpus. | 3. The non-transitory storage medium as set forth in claim 2 , wherein the performing LDA comprises: performing LDA with an IBP compound Dirichlet prior probability distribution configured such that the inferred topic model associates a focused sub-set of the set of topics to each document of the training corpus. 4. The non-transitory storage medium as set forth in claim 3 , wherein the method further comprises: selecting a document of the training corpus of documents; and identifying at least one other document of the training corpus of documents that is similar to the selected document based on the focused sub-sets of the set of topics associated to the documents of the training corpus by the inferred topic model. | 0.821273 |
9,244,887 | 16 | 45 | 16. The method of claim 1 , wherein determining an optimal time series frequency includes aggregating the unstructured time-stamped data into aggregated time-stamped data using the time series engine, and wherein the aggregating is performed using a potential hierarchical structure and a plurality of candidate frequencies for the potential hierarchical structure. | 16. The method of claim 1 , wherein determining an optimal time series frequency includes aggregating the unstructured time-stamped data into aggregated time-stamped data using the time series engine, and wherein the aggregating is performed using a potential hierarchical structure and a plurality of candidate frequencies for the potential hierarchical structure. 45. The machine-readable non-transitory storage medium of claim 16 , further comprising instructions configured to cause a data processing system to perform operations including: providing a first portion of the derived time series to a first processor for performing a statistical analysis; and providing a second portion of the derived time series to a second processor for performing the statistical analysis, wherein the first portion and the second portion are based upon a portion of a hierarchy in which the first portion and the second portion reside. | 0.875167 |
8,375,067 | 21 | 23 | 21. A system comprising: a plurality of processors; a database; a matching module implemented on one of the plurality of processors connected to the database and to a web server accessible to a job seeker, said matching module determining a matched job for the job seeker by comparing job parameters and job seeker parameters; an individualized data collection module determining job seeker characteristics based on individualized information captured from a user interface instantiated on a job seeker's individual device, wherein the determined job seeker characteristics are incorporated into job seeker parameters utilized by the matching module; a correlation module implemented on one of the plurality of processors communicating with the job matching module and the database, the correlation module comprising: a user activity monitor module implemented on one of the plurality of processors tracking job seeker activity within the system for matching job seekers with potential jobs based on behavior of prior activity for the job seeker; an affinity module implemented on one of the plurality of processors configured to determine affinity metrics between the matched job and other jobs interacted with by other job seekers based on the tracked job seeker activity and determine alternative jobs in addition to the matched job for the job seeker based on the determined affinity metrics; and a filtration module implemented on one of the plurality of processors operably coupled to the affinity module and user activity monitor module receiving preferences from a job seeker to refine correlations made by the matching module and correlation module for consideration by the job seeker, and generating and storing a negative filtration indication associated with a job for excluding the job in instant and subsequent job queries for the job seeker. | 21. A system comprising: a plurality of processors; a database; a matching module implemented on one of the plurality of processors connected to the database and to a web server accessible to a job seeker, said matching module determining a matched job for the job seeker by comparing job parameters and job seeker parameters; an individualized data collection module determining job seeker characteristics based on individualized information captured from a user interface instantiated on a job seeker's individual device, wherein the determined job seeker characteristics are incorporated into job seeker parameters utilized by the matching module; a correlation module implemented on one of the plurality of processors communicating with the job matching module and the database, the correlation module comprising: a user activity monitor module implemented on one of the plurality of processors tracking job seeker activity within the system for matching job seekers with potential jobs based on behavior of prior activity for the job seeker; an affinity module implemented on one of the plurality of processors configured to determine affinity metrics between the matched job and other jobs interacted with by other job seekers based on the tracked job seeker activity and determine alternative jobs in addition to the matched job for the job seeker based on the determined affinity metrics; and a filtration module implemented on one of the plurality of processors operably coupled to the affinity module and user activity monitor module receiving preferences from a job seeker to refine correlations made by the matching module and correlation module for consideration by the job seeker, and generating and storing a negative filtration indication associated with a job for excluding the job in instant and subsequent job queries for the job seeker. 23. The system according to claim 21 wherein the filtration module communicates with the user activity monitor module to ensure subsequent matching results do not include a matching job selected by the job seeker for elimination. | 0.59965 |
8,515,816 | 22 | 24 | 22. The method of claim 1 wherein the collective analysis comprises analyzing interactions with a distinguished document, the method further comprising modifying the distinguished document based upon the analysis of interactions with the distinguished document. | 22. The method of claim 1 wherein the collective analysis comprises analyzing interactions with a distinguished document, the method further comprising modifying the distinguished document based upon the analysis of interactions with the distinguished document. 24. The method of claim 22 wherein the collective analysis determines that the frequency of text captures from a distinguished portion of the distinguished document is higher than a pre-determined frequency, and wherein the distinguished document is modified by expanding the distinguished portion. | 0.827546 |
7,756,930 | 50 | 53 | 50. The machine-readable storage medium of claim 45 , further comprising instructions which, when executed by the one or more processors, cause the one or more processors to carry out the step of: when the reputation score is better than the first predefined threshold and worse than the second predefined threshold, performing a third specified action. | 50. The machine-readable storage medium of claim 45 , further comprising instructions which, when executed by the one or more processors, cause the one or more processors to carry out the step of: when the reputation score is better than the first predefined threshold and worse than the second predefined threshold, performing a third specified action. 53. The machine-readable storage medium of claim 50 , wherein the message is associated with a message recipient, and wherein the step of performing the third specified action comprises sending the message to the message recipient. | 0.933773 |
8,856,132 | 28 | 29 | 28. The computer program product of claim 26 , wherein the one of more data points comprise one or more of identity information of the first member, a project to which the knowledge tip is associated, date and time at which the knowledge tip is received by the tips repository and a rating. | 28. The computer program product of claim 26 , wherein the one of more data points comprise one or more of identity information of the first member, a project to which the knowledge tip is associated, date and time at which the knowledge tip is received by the tips repository and a rating. 29. The computer program product of claim 28 further comprising program instructions for determining the rating based on feedback from one or more members viewing the knowledge tip. | 0.966294 |
9,110,923 | 1 | 3 | 1. A computer-implemented method comprising: receiving a search query; identifying a lookup table corresponding to the search query; for each image in a collection of images: generating an image hash for the image based on one or more features extracted from the image, wherein the image hash comprises a plurality of hash characters, and computing a score for the image hash using the lookup table, wherein computing the score for each image hash comprises summing lookup table weights for each hash character of the plurality of hash characters, and wherein the lookup table includes a first index that corresponds to the lookup table value of each hash character, and a second index that corresponds to a position of each hash character in the image hash; ordering the images by the score of each image hash; and providing a group of the ordered images as search results responsive to the search query. | 1. A computer-implemented method comprising: receiving a search query; identifying a lookup table corresponding to the search query; for each image in a collection of images: generating an image hash for the image based on one or more features extracted from the image, wherein the image hash comprises a plurality of hash characters, and computing a score for the image hash using the lookup table, wherein computing the score for each image hash comprises summing lookup table weights for each hash character of the plurality of hash characters, and wherein the lookup table includes a first index that corresponds to the lookup table value of each hash character, and a second index that corresponds to a position of each hash character in the image hash; ordering the images by the score of each image hash; and providing a group of the ordered images as search results responsive to the search query. 3. The method of claim 1 , wherein each hash character corresponds to a bit string. | 0.945538 |
8,909,513 | 9 | 16 | 9. A system comprising: one or more computers programmed to perform operations comprising: selecting one or more segments from a text field, wherein each of the segments is in proximity to a current position of an input cursor in the text field; analyzing the segments to determine a respective context for each of the segments, wherein the context is at least one of a respective target subtext or a respective target meaning of the segment; for one or more of the segments, identifying a respective candidate emoticon for the segment based on an association between the candidate emoticon and the context of the segment, the association exceeding a threshold value and being based on, at least, statistical usage of the candidate emoticon for the context by one or more users, wherein a strength of the association varies according to the statistical usage; providing one or more of the candidate emoticons for user selection, the candidate emoticons for user selection being based on at least one of a user preference, user-related information, and recipient-related information; receiving user selection of one or more of the provided emoticons and inserting the selected emoticons into the text field at the current position of the input cursor; and updating the statistical usage of at least one of the provided emoticons based on the user selection. | 9. A system comprising: one or more computers programmed to perform operations comprising: selecting one or more segments from a text field, wherein each of the segments is in proximity to a current position of an input cursor in the text field; analyzing the segments to determine a respective context for each of the segments, wherein the context is at least one of a respective target subtext or a respective target meaning of the segment; for one or more of the segments, identifying a respective candidate emoticon for the segment based on an association between the candidate emoticon and the context of the segment, the association exceeding a threshold value and being based on, at least, statistical usage of the candidate emoticon for the context by one or more users, wherein a strength of the association varies according to the statistical usage; providing one or more of the candidate emoticons for user selection, the candidate emoticons for user selection being based on at least one of a user preference, user-related information, and recipient-related information; receiving user selection of one or more of the provided emoticons and inserting the selected emoticons into the text field at the current position of the input cursor; and updating the statistical usage of at least one of the provided emoticons based on the user selection. 16. The system of claim 9 wherein the recipient-related information includes a recipient's relation to a user, a recipient interest, a recipient ethnicity, a recipient religion, a recipient geographic location, a recipient age, a recipient relational status, and a recipient occupation. | 0.665888 |
8,706,644 | 2 | 7 | 2. A method implemented at least in part by a computing device, the method comprising: responsive to determining that a corpus of text includes a statistically improbable phrase, storing the determined statistically improbable phrase in a corpus of phrases for association with a user account, wherein the statistically improbable phrase, when received before or during a transaction, provides access to a payment instrument for use in a transaction; and causing output of the stored statistically improbable phrase for association with a user account. | 2. A method implemented at least in part by a computing device, the method comprising: responsive to determining that a corpus of text includes a statistically improbable phrase, storing the determined statistically improbable phrase in a corpus of phrases for association with a user account, wherein the statistically improbable phrase, when received before or during a transaction, provides access to a payment instrument for use in a transaction; and causing output of the stored statistically improbable phrase for association with a user account. 7. A method as recited in claim 2 , further comprising: determining at least one keyword associated with a user of the user account; determining phrases of the corpus of phrases that are associated with the at least one keyword; if the phrases determined to be associated with the at least one keyword include the statistically improbable phrase, suggesting the statistically improbable phrase to the user; and otherwise, suggesting one or more phrases other than the statistically improbable phrase to the user. | 0.699883 |
9,442,922 | 1 | 15 | 1. A method for updating a reordering model of a statistical machine translation system comprising: at a first time, receiving new training data for retraining an existing statistical machine translation system, the new training data comprising at least one sentence pair, each of the at least one sentence pair comprising a source sentence in a source language and a target sentence in a target language; extracting phrase pairs from the new training data, each phrase pair including a source language phrase and a target language phrase; generating a new reordering file from the extracted phrase pairs, the new reordering file including a set of the phrase pairs extracted from the new training data; updating a reordering model of the existing statistical machine translation system based on the new reordering file, the reordering model including a reordering table, the reordering table comprising phrase pairs and a set of features, the set of features comprising, for each of a set of orientation types, at least one feature which is a function of a count of the orientation type for the respective phrase pair, each phrase pair in the reordering table occurring only once, and wherein the updating of the reordering model includes merging an existing reordering table with the new reordering file or merging the existing reordering table with a new reordering table generated from the new reordering file, the merging including updating feature scores for each of the orientation types for at least some of the phrase pairs based on the counts stored in the existing reordering table; at a second time after the first time, receiving new training data for training the existing statistical machine translation system, the new training data comprising at least one sentence pair, the sentence pair comprising a source sentence in the source language and a target sentence in the target language; and reiterating the extracting of phrase pairs, generating of the new reordering file and the updating the reordering model based on the new training data received at the second time, wherein at least one of the extracting phrase pairs, generating the new reordering file, and updating the reordering model is performed with a computer processor. | 1. A method for updating a reordering model of a statistical machine translation system comprising: at a first time, receiving new training data for retraining an existing statistical machine translation system, the new training data comprising at least one sentence pair, each of the at least one sentence pair comprising a source sentence in a source language and a target sentence in a target language; extracting phrase pairs from the new training data, each phrase pair including a source language phrase and a target language phrase; generating a new reordering file from the extracted phrase pairs, the new reordering file including a set of the phrase pairs extracted from the new training data; updating a reordering model of the existing statistical machine translation system based on the new reordering file, the reordering model including a reordering table, the reordering table comprising phrase pairs and a set of features, the set of features comprising, for each of a set of orientation types, at least one feature which is a function of a count of the orientation type for the respective phrase pair, each phrase pair in the reordering table occurring only once, and wherein the updating of the reordering model includes merging an existing reordering table with the new reordering file or merging the existing reordering table with a new reordering table generated from the new reordering file, the merging including updating feature scores for each of the orientation types for at least some of the phrase pairs based on the counts stored in the existing reordering table; at a second time after the first time, receiving new training data for training the existing statistical machine translation system, the new training data comprising at least one sentence pair, the sentence pair comprising a source sentence in the source language and a target sentence in the target language; and reiterating the extracting of phrase pairs, generating of the new reordering file and the updating the reordering model based on the new training data received at the second time, wherein at least one of the extracting phrase pairs, generating the new reordering file, and updating the reordering model is performed with a computer processor. 15. The method of claim 1 , wherein the new reordering file includes only phrase pairs extracted from the new training data. | 0.817109 |
4,122,444 | 7 | 16 | 7. An apparatus in accordance with claim 1, wherein said plurality of different sets of numeral characters comprises a first and second set thereof, and said display means comprises a first display means portion responsive to said first set of element select signals for displaying said numerical value information by said first set of numeral characters; and a second display means portion responsive to said second set of element select signals for displaying said numerical value information by said second set of numeral characters. | 7. An apparatus in accordance with claim 1, wherein said plurality of different sets of numeral characters comprises a first and second set thereof, and said display means comprises a first display means portion responsive to said first set of element select signals for displaying said numerical value information by said first set of numeral characters; and a second display means portion responsive to said second set of element select signals for displaying said numerical value information by said second set of numeral characters. 16. An apparatus in accordance with claim 7, which further comprises means operatively associated with said converting means for selectively withdrawing one of said first and second kinds of element select signals for representing said coded numerical value information by a selected group of said first and second different kinds of groups of numeral characters, respectively, and wherein said display means is adapted to display said numerical value information by said selected group of said first and second different kinds of groups of numeral characters. | 0.864407 |
8,095,565 | 19 | 20 | 19. An apparatus for rendering a user interface using metadata, comprising: a processor and a computer-readable medium; an operating environment stored on the computer-readable medium and executing on the processor; a data store that is configured to store a metadata file that specifies controls within a user interface that are each wrapped by a wrapper class that provides functionality for data binding and exposing properties of the control and wherein the metadata within the file includes binding expressions that are used to bind data to one or more controls of the user interface, the binding expressions including a data source; wherein the binding expressions may be used to propagate changes back to the data source from the user interface; wherein the metadata for one or more of the controls expose an event by specifying within the metadata a name of an event and a method name for handling the event; and a rendering engine comprising functionality that is configured to interpret the metadata and render the user interface according to the metadata. | 19. An apparatus for rendering a user interface using metadata, comprising: a processor and a computer-readable medium; an operating environment stored on the computer-readable medium and executing on the processor; a data store that is configured to store a metadata file that specifies controls within a user interface that are each wrapped by a wrapper class that provides functionality for data binding and exposing properties of the control and wherein the metadata within the file includes binding expressions that are used to bind data to one or more controls of the user interface, the binding expressions including a data source; wherein the binding expressions may be used to propagate changes back to the data source from the user interface; wherein the metadata for one or more of the controls expose an event by specifying within the metadata a name of an event and a method name for handling the event; and a rendering engine comprising functionality that is configured to interpret the metadata and render the user interface according to the metadata. 20. The apparatus of claim 19 , wherein the metadata is created according to a metadata schema that includes mechanisms to: create the controls within the user interface; programmatically modify the controls and support event handling for the controls. | 0.501976 |
9,396,192 | 1 | 3 | 1. A method for tagging a media asset, the method comprising: receiving, with control circuitry, a plurality of communications from a plurality of users, wherein each of the plurality of communications includes words spoken by a respective one of the users while accessing the media asset, and wherein each of the communications is associated with a media asset play position during which the respective words were spoken; selecting a subset of the plurality of communications for which the associated media asset play position is within a range of play positions, the range of play positions being shorter than a duration of the media asset; identifying, with the control circuitry, a word that a threshold number of the selected communications have in common; retrieving from an attribute database an attribute associated with the word; and assigning the retrieved attribute to the media asset within the range of play positions. | 1. A method for tagging a media asset, the method comprising: receiving, with control circuitry, a plurality of communications from a plurality of users, wherein each of the plurality of communications includes words spoken by a respective one of the users while accessing the media asset, and wherein each of the communications is associated with a media asset play position during which the respective words were spoken; selecting a subset of the plurality of communications for which the associated media asset play position is within a range of play positions, the range of play positions being shorter than a duration of the media asset; identifying, with the control circuitry, a word that a threshold number of the selected communications have in common; retrieving from an attribute database an attribute associated with the word; and assigning the retrieved attribute to the media asset within the range of play positions. 3. The method of claim 1 , wherein the attribute is different from the identified word. | 0.837079 |
6,161,130 | 12 | 13 | 12. The method in claim 9 wherein the handcrafted features comprise features correspondingly related to formatting, authoring, delivery or communication attributes that characterize a message as belonging to the first class. | 12. The method in claim 9 wherein the handcrafted features comprise features correspondingly related to formatting, authoring, delivery or communication attributes that characterize a message as belonging to the first class. 13. The method in claim 12 wherein the formatting attributes comprises whether a predefined word in the text of the incoming message is capitalized, or whether the text of the incoming message contains a series of predefined punctuation marks. | 0.920432 |
Subsets and Splits
No saved queries yet
Save your SQL queries to embed, download, and access them later. Queries will appear here once saved.