Invention Grant
- Patent Title: Mapping natural language and code segments
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Application No.: US17337634Application Date: 2021-06-03
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Publication No.: US11645054B2Publication Date: 2023-05-09
- Inventor: Zhong Fang Yuan , Bin Shang , Li Ni Zhang , Yong Fang Liang , Chen Gao , Tong Liu
- Applicant: International Business Machines Corporation
- Applicant Address: US NY Armonk
- Assignee: International Business Machines Corporation
- Current Assignee: International Business Machines Corporation
- Current Assignee Address: US NY Armonk
- Agency: Patterson + Sheridan, LLP
- Main IPC: G06F9/44
- IPC: G06F9/44 ; G06F8/41 ; G06F8/36 ; G06F40/279 ; G06N20/00 ; G06N3/04 ; G06F8/75

Abstract:
Techniques are provided for mapping natural language to code segments. In one embodiment, the techniques involve receiving a document and software code, wherein the document comprises a natural language description of a use of the code, generating, via a vectorization process performed on the document, at least one vector or word embedding, generating, via a natural language processing technique performed on the at least one vector or word embedding, a first label set, generating, via a machine learning analysis of the software code, a second label set, determining, based on a comparison of the first label set and the second label set, a match confidence between the document and the software code, wherein the match confidence indicates a measure of similarity between the first label set and the second label set, and upon determining that the match confidence exceeds a predefined threshold, mapping the document to the software code.
Public/Granted literature
- US20220391183A1 MAPPING NATURAL LANGUAGE AND CODE SEGMENTS Public/Granted day:2022-12-08
Information query