Text embedding-based search taxonomy generation and intelligent refinement
Various embodiments of the present disclosure provide computer interpretation techniques for implementing a query resolution process to improve upon traditional search resolutions within a search domain. The techniques may include generating a plurality of interaction embeddings for a plurality of t...
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creator | Anushiravani, Ramin Fan, Zengpan Savle, Ketki Karim, Fazle Shahnawaz Muhibul Ni, Yizhao Tomar, Ayush |
description | Various embodiments of the present disclosure provide computer interpretation techniques for implementing a query resolution process to improve upon traditional search resolutions within a search domain. The techniques may include generating a plurality of interaction embeddings for a plurality of textual descriptions corresponding to a plurality of interaction codes identified within an interaction dataset and a plurality of taxonomy embeddings for a plurality of taxonomy categories identified within a taxonomy dataset. The techniques may include generating similarity scores for a plurality of description-category pairs based on a comparison between the plurality of interaction embeddings and the plurality of taxonomy embeddings. The techniques may include generating an enhanced taxonomy by augmenting one or more of the plurality of taxonomy categories with one or more of the plurality of textual descriptions based on the similarity scores and initiating, using the enhanced taxonomy, the performance of a query resolution operation. |
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The techniques may include generating an enhanced taxonomy by augmenting one or more of the plurality of taxonomy categories with one or more of the plurality of textual descriptions based on the similarity scores and initiating, using the enhanced taxonomy, the performance of a query resolution operation.</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>ELECTRIC DIGITAL DATA PROCESSING</subject><subject>PHYSICS</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2024</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNrjZPAKSa0oUUjNTUpNScnMS9dNSixOTVEoTk0sSs5QKEmsyM_Lz61USE_NSy1KLMnMz1NIzEtRyMwrSc3JyQSKligUpaZl5qXmApk8DKxpiTnFqbxQmptB0c01xNlDN7UgPz61uCAxGWhKSXxosKGRoYmhoYWZk6ExMWoAYBw1ww</recordid><startdate>20241112</startdate><enddate>20241112</enddate><creator>Anushiravani, Ramin</creator><creator>Fan, Zengpan</creator><creator>Savle, Ketki</creator><creator>Karim, Fazle Shahnawaz Muhibul</creator><creator>Ni, Yizhao</creator><creator>Tomar, Ayush</creator><scope>EVB</scope></search><sort><creationdate>20241112</creationdate><title>Text embedding-based search taxonomy generation and intelligent refinement</title><author>Anushiravani, Ramin ; Fan, Zengpan ; Savle, Ketki ; Karim, Fazle Shahnawaz Muhibul ; Ni, Yizhao ; Tomar, Ayush</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_US12141186B13</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>eng</language><creationdate>2024</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>ELECTRIC DIGITAL DATA PROCESSING</topic><topic>PHYSICS</topic><toplevel>online_resources</toplevel><creatorcontrib>Anushiravani, Ramin</creatorcontrib><creatorcontrib>Fan, Zengpan</creatorcontrib><creatorcontrib>Savle, Ketki</creatorcontrib><creatorcontrib>Karim, Fazle Shahnawaz Muhibul</creatorcontrib><creatorcontrib>Ni, Yizhao</creatorcontrib><creatorcontrib>Tomar, Ayush</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Anushiravani, Ramin</au><au>Fan, Zengpan</au><au>Savle, Ketki</au><au>Karim, Fazle Shahnawaz Muhibul</au><au>Ni, Yizhao</au><au>Tomar, Ayush</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>Text embedding-based search taxonomy generation and intelligent refinement</title><date>2024-11-12</date><risdate>2024</risdate><abstract>Various embodiments of the present disclosure provide computer interpretation techniques for implementing a query resolution process to improve upon traditional search resolutions within a search domain. The techniques may include generating a plurality of interaction embeddings for a plurality of textual descriptions corresponding to a plurality of interaction codes identified within an interaction dataset and a plurality of taxonomy embeddings for a plurality of taxonomy categories identified within a taxonomy dataset. The techniques may include generating similarity scores for a plurality of description-category pairs based on a comparison between the plurality of interaction embeddings and the plurality of taxonomy embeddings. The techniques may include generating an enhanced taxonomy by augmenting one or more of the plurality of taxonomy categories with one or more of the plurality of textual descriptions based on the similarity scores and initiating, using the enhanced taxonomy, the performance of a query resolution operation.</abstract><oa>free_for_read</oa></addata></record> |
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subjects | CALCULATING COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING PHYSICS |
title | Text embedding-based search taxonomy generation and intelligent refinement |
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