Invention Grant
- Patent Title: Semantic map generation from natural-language-text documents
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Application No.: US17337239Application Date: 2021-06-02
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Publication No.: US11238240B2Publication Date: 2022-02-01
- Inventor: Edward Hunter
- Applicant: Digital Asset Capital, Inc.
- Applicant Address: US MD Gaithersburg
- Assignee: Digital Asset Capital, Inc.
- Current Assignee: Digital Asset Capital, Inc.
- Current Assignee Address: US MD Gaithersburg
- Agency: Pillsbury Winthrop Shaw Pittman, LLP
- Main IPC: G06F17/00
- IPC: G06F17/00 ; G06F40/30 ; G06F40/284 ; G06N20/00 ; G06F40/103

Abstract:
A computer-implemented process includes obtaining a natural-language-text document comprising a first and second clause and determining first and second embedding sequences based on n-grams of the first and second clauses. The process includes generating data model objects based on the embedding sequences and determining an association between the first data model object and the second data model object based on a shared parameter of the first and second clauses. The process includes receiving a query including the first category and the first n-gram and causing a presentation of a visualization of data model objects that includes shapes based on the data model objects and a third shape based on the association between the first data model object and the second data model object.
Public/Granted literature
- US20210383070A1 SEMANTIC MAP GENERATION FROM NATURAL-LANGUAGE-TEXT DOCUMENTS Public/Granted day:2021-12-09
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