Invention Grant
- Patent Title: Combining chemical structure data with unstructured data for predictive analytics in a cognitive system
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Application No.: US16444131Application Date: 2019-06-18
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Publication No.: US11100413B2Publication Date: 2021-08-24
- Inventor: William S. Spangler , Richard L. Martin , Feng Wang , Xiaoyang Gao , Sheng Hua Bao
- 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: Edell, Shapiro & Finnan, LLC
- Agent Will Stock
- Main IPC: G06F3/048
- IPC: G06F3/048 ; G06N5/04 ; G06N20/00 ; G06F16/338 ; G06F16/33 ; G16C20/70

Abstract:
According to embodiments of the present invention, an entity may be represented by an unstructured feature vector comprising a plurality of features extracted from unstructured data using semantic analysis and a structural feature vector comprising a plurality of features from chemical structure data. A similarity matrix may be used to compare entities and generate a similarity score, based on both the unstructured feature vector and the structural feature vector for each entity. In some aspects, a user may enter a query (from which a chemical structural feature vector is dynamically generated) to compare against entities having unstructured and/or structural feature vectors, stored in a database.
Public/Granted literature
- US20190303780A1 COMBINING CHEMICAL STRUCTURE DATA WITH UNSTRUCTURED DATA FOR PREDICTIVE ANALYTICS IN A COGNITIVE SYSTEM Public/Granted day:2019-10-03
Information query