Invention Grant
- Patent Title: Machine learning techniques for determining predicted similarity scores for input sequences
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Application No.: US17560491Application Date: 2021-12-23
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Publication No.: US11948378B2Publication Date: 2024-04-02
- Inventor: Subhodeep Dey , Brad Booher , Edward Sverdlin , Reshma S. Ombase , Raghvendra Kumar Yadav
- Applicant: UnitedHealth Group Incorporated
- Applicant Address: US MN Minnetonka
- Assignee: UnitedHealth Group Incorporated
- Current Assignee: UnitedHealth Group Incorporated
- Current Assignee Address: US MN Minnetonka
- Agency: Alston & Bird LLP
- Main IPC: G06V30/00
- IPC: G06V30/00 ; G06V10/82 ; G06V30/19
Abstract:
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.
Public/Granted literature
- US20230206666A1 MACHINE LEARNING TECHNIQUES FOR DETERMINING PREDICTED SIMILARITY SCORES FOR INPUT SEQUENCES Public/Granted day:2023-06-29
Information query
