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US Patent 11966699 Intent classification using non-correlated features

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Is a
Patent
Patent
0

Patent attributes

Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
0
Patent Number
119666990
Patent Inventor Names
Lin Pan0
Saloni Potdar0
Ladislav Kunc0
Haode Qi0
Abhishek Shah0
Date of Patent
April 23, 2024
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Patent Application Number
173501160
Date Filed
June 17, 2021
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Patent Citations
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US Patent 9740987 Generation of computer-based discovery avatars based on tokenization of prioritized source data
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US Patent 10528407 Integrated statistical log data mining for mean time auto-resolution
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US Patent 11288453 Key-word identification
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US Patent 10606931 Systems and methods for scalable hierarchical coreference
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US Patent 11392772 Coding information extractor
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US Patent 8478749 Method and apparatus for determining relevant search results using a matrix framework
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US Patent 9208134 Methods and systems for tokenizing multilingual textual documents
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Patent Primary Examiner
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Richard Z Zhu
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Patent abstract

A system for classifying a language sample intent by receiving a language sample including a set of features, identifying language sample features, determining a tokenization score for the language sample according to the language sample features, eliminating duplicate features according to the tokenization score, determining a term frequency (tf) according to the identified features and the tokenization score, determining an inverse document frequency (idf) according to the identified features and the tokenization score, and generating a term frequency-inverse document frequency (tf-idf) matrix for the identified features.

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