- 专利标题： Machine learning techniques for determining predicted similarity scores for input sequences
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申请号： US17560491申请日： 2021-12-23
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公开(公告)号： US11948378B2公开(公告)日： 2024-04-02
- 发明人: Subhodeep Dey , Brad Booher , Edward Sverdlin , Reshma S. Ombase , Raghvendra Kumar Yadav
- 申请人： UnitedHealth Group Incorporated
- 申请人地址： US MN Minnetonka
- 专利权人： UnitedHealth Group Incorporated
- 当前专利权人： UnitedHealth Group Incorporated
- 当前专利权人地址： US MN Minnetonka
- 代理机构： Alston & Bird LLP
- 主分类号： G06V30/00
- IPC分类号： G06V30/00 ; G06V10/82 ; G06V30/19
摘要：
Systems and methods for dynamically generating a predicted similarity score for a pair of input sequences. A predicted similarity score for a pair of input sequences is determined based at least in part on at least one of a token-level similarity probability score for the pair of input sequences, a target region match indication for the pair of input sequences, a fuzzy match score for the pair of input sequences, a character-level match score for the pair of input sequences, one or more similarity ratio occurrence indicators for the pair of input sequences, and a harmonic mean score of the fuzzy match score for the pair of input sequences and the token-level similarity probability score for the pair of input sequences.
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