Cognitive generation of tailored analogies
An embodiment includes processing a dataset to generate a set of feature vectors that include a first feature vector corresponding to a first concept within a user's areas of interest and a second feature vector corresponding to a second concept within the user's areas of study. The embodi...
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| creator | Ravizza, Stefan Kwatra, Shikhar Flöther, Frederik Frank Loredo, Robert E |
| description | An embodiment includes processing a dataset to generate a set of feature vectors that include a first feature vector corresponding to a first concept within a user's areas of interest and a second feature vector corresponding to a second concept within the user's areas of study. The embodiment identifies clusters of the feature vectors and identifies key features that most contribute to influencing the clustering algorithm. The embodiment selects the first feature vector in response to a user query, and then selects the second feature vector based on an overlap between key features of the first and second feature vectors and a degree of dissimilarity between the first and second concepts. The embodiment outputs a query response that includes the second concept. The embodiment also determines an effectiveness value based on sensor data indicative of a user action responsive to the outputting of the response to the query. |
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The embodiment identifies clusters of the feature vectors and identifies key features that most contribute to influencing the clustering algorithm. The embodiment selects the first feature vector in response to a user query, and then selects the second feature vector based on an overlap between key features of the first and second feature vectors and a degree of dissimilarity between the first and second concepts. The embodiment outputs a query response that includes the second concept. The embodiment also determines an effectiveness value based on sensor data indicative of a user action responsive to the outputting of the response to the query.</description><language>eng</language><subject>ACOUSTICS ; CALCULATING ; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS ; COMPUTING ; COUNTING ; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ; ELECTRIC DIGITAL DATA PROCESSING ; MUSICAL INSTRUMENTS ; PHYSICS ; SPEECH ANALYSIS OR SYNTHESIS ; SPEECH OR AUDIO CODING OR DECODING ; SPEECH OR VOICE PROCESSING ; SPEECH RECOGNITION ; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><creationdate>2024</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240326&DB=EPODOC&CC=US&NR=11941000B2$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25564,76547</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20240326&DB=EPODOC&CC=US&NR=11941000B2$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>Ravizza, Stefan</creatorcontrib><creatorcontrib>Kwatra, Shikhar</creatorcontrib><creatorcontrib>Flöther, Frederik Frank</creatorcontrib><creatorcontrib>Loredo, Robert E</creatorcontrib><title>Cognitive generation of tailored analogies</title><description>An embodiment includes processing a dataset to generate a set of feature vectors that include a first feature vector corresponding to a first concept within a user's areas of interest and a second feature vector corresponding to a second concept within the user's areas of study. The embodiment identifies clusters of the feature vectors and identifies key features that most contribute to influencing the clustering algorithm. The embodiment selects the first feature vector in response to a user query, and then selects the second feature vector based on an overlap between key features of the first and second feature vectors and a degree of dissimilarity between the first and second concepts. The embodiment outputs a query response that includes the second concept. The embodiment also determines an effectiveness value based on sensor data indicative of a user action responsive to the outputting of the response to the query.</description><subject>ACOUSTICS</subject><subject>CALCULATING</subject><subject>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>MUSICAL INSTRUMENTS</subject><subject>PHYSICS</subject><subject>SPEECH ANALYSIS OR SYNTHESIS</subject><subject>SPEECH OR AUDIO CODING OR DECODING</subject><subject>SPEECH OR VOICE PROCESSING</subject><subject>SPEECH RECOGNITION</subject><subject>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZNByzk_PyyzJLEtVSE_NSy1KLMnMz1PIT1MoSczMyS9KTVFIzEvMyU_PTC3mYWBNS8wpTuWF0twMim6uIc4euqkF-fGpxQWJyUADSuJDgw0NLU0MDQwMnIyMiVEDAE0DKVU</recordid><startdate>20240326</startdate><enddate>20240326</enddate><creator>Ravizza, Stefan</creator><creator>Kwatra, Shikhar</creator><creator>Flöther, Frederik Frank</creator><creator>Loredo, Robert E</creator><scope>EVB</scope></search><sort><creationdate>20240326</creationdate><title>Cognitive generation of tailored analogies</title><author>Ravizza, Stefan ; Kwatra, Shikhar ; Flöther, Frederik Frank ; Loredo, Robert E</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US11941000B23</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2024</creationdate><topic>ACOUSTICS</topic><topic>CALCULATING</topic><topic>COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>MUSICAL INSTRUMENTS</topic><topic>PHYSICS</topic><topic>SPEECH ANALYSIS OR SYNTHESIS</topic><topic>SPEECH OR AUDIO CODING OR DECODING</topic><topic>SPEECH OR VOICE PROCESSING</topic><topic>SPEECH RECOGNITION</topic><topic>SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR</topic><toplevel>online_resources</toplevel><creatorcontrib>Ravizza, Stefan</creatorcontrib><creatorcontrib>Kwatra, Shikhar</creatorcontrib><creatorcontrib>Flöther, Frederik Frank</creatorcontrib><creatorcontrib>Loredo, Robert E</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Ravizza, Stefan</au><au>Kwatra, Shikhar</au><au>Flöther, Frederik Frank</au><au>Loredo, Robert E</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Cognitive generation of tailored analogies</title><date>2024-03-26</date><risdate>2024</risdate><abstract>An embodiment includes processing a dataset to generate a set of feature vectors that include a first feature vector corresponding to a first concept within a user's areas of interest and a second feature vector corresponding to a second concept within the user's areas of study. The embodiment identifies clusters of the feature vectors and identifies key features that most contribute to influencing the clustering algorithm. The embodiment selects the first feature vector in response to a user query, and then selects the second feature vector based on an overlap between key features of the first and second feature vectors and a degree of dissimilarity between the first and second concepts. The embodiment outputs a query response that includes the second concept. The embodiment also determines an effectiveness value based on sensor data indicative of a user action responsive to the outputting of the response to the query.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | ACOUSTICS CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES ELECTRIC DIGITAL DATA PROCESSING MUSICAL INSTRUMENTS PHYSICS SPEECH ANALYSIS OR SYNTHESIS SPEECH OR AUDIO CODING OR DECODING SPEECH OR VOICE PROCESSING SPEECH RECOGNITION SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR |
| title | Cognitive generation of tailored analogies |
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