发明授权
- 专利标题: Systems and methods for assessing quality of input text using recurrent neural networks
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申请号: US15793281申请日: 2017-10-25
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公开(公告)号: US11151130B2公开(公告)日: 2021-10-19
- 发明人: Robin Tommy , Sarath Sivaprasad
- 申请人: Tata Consultancy Services Limited
- 申请人地址: IN Mumbai
- 专利权人: Tata Consultancy Services Limited
- 当前专利权人: Tata Consultancy Services Limited
- 当前专利权人地址: IN Mumbai
- 代理机构: Finnegan, Henderson, Farabow, Garrett & Dunner, LLP
- 优先权: IN201721004117 20170204
- 主分类号: G06F16/242
- IPC分类号: G06F16/242 ; G06F16/245 ; G06F16/30 ; G06F16/93 ; G06F40/30 ; G06F40/232 ; G06F16/33 ; G06F16/2455 ; G06F16/2453 ; G06F16/35 ; G06F16/2457 ; G06N3/02
摘要:
Systems and methods for assessing quality of input text using recurrent neural networks is disclosed. The system obtains input text from user and performs a comparison of each word from input text with words from dictionary (or trained data) to determine a closest recommended word for each word in the input text. The input text is further analyzed to determine context of each word based on at least a portion of input text, and based on determined context, at least one of correct sentences, incorrect sentences, and/or complex sentences are determined from the input text. Each word is converted to a vector based on concept(s) by comparing each word across sentences of input text to generate vectors set, and quality of the input text is assessed based on vectors set, the comparison, determined context and at least one of correct sentences, incorrect sentences, complex sentences, or combinations thereof.
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