Invention Grant
- Patent Title: Triangulated natural language decoding from forecasted deep semantic representations
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Application No.: US16670773Application Date: 2019-10-31
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Publication No.: US11308285B2Publication Date: 2022-04-19
- Inventor: Aaron K. Baughman , Micah Forster , John C. Newell , Stephen C. Hammer
- 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: Cantor Colburn LLP
- Agent Christopher Pignato
- Main IPC: G06F17/00
- IPC: G06F17/00 ; G06F40/30 ; G06F16/33 ; G06F40/295

Abstract:
Computer-implemented method includes developing, via a processor, a words model from a plurality of natural language text based articles relating to a subject and generating, via the processor, a static vector based upon the words model. The computer-implemented method further includes developing, via the processor, an actual articles model from actual articles, generating, via the processor, a bootstrapped vector using the actual articles model, generating, via the processor, a n-dimensional depth item using the static vector and the bootstrapped vector, and determining, via the processor, evidence based on the n-dimensional depth item. The computer-implemented method still further includes presenting, via the processor and a display, the evidence base upon an input query from a user.
Public/Granted literature
- US20210133288A1 TRIANGULATED NATURAL LANGUAGE DECODING FROM FORECASTED DEEP SEMANTIC REPRESENTATIONS Public/Granted day:2021-05-06
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