Invention Grant
- Patent Title: Machine learning for ranking candidate subjects based on a training set
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Application No.: US15625352Application Date: 2017-06-16
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Publication No.: US11182692B2Publication Date: 2021-11-23
- Inventor: Alix M. Lacoste , William S. Spangler
- 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 John Noh
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G16H50/70

Abstract:
According to an embodiment of the present invention, a system designates each document in a collection of documents as a member of a first group containing known subjects for a concept of interest or as a member of a second group containing candidate subjects for the concept of interest and determines a subset of documents for at least one subject. The system generates a classifier based on the documents in the first and second groups and applies the classifier to a set of documents for the at least one subject to determine whether each document belong to the first and/or second group. The system generates a score for the at least one subject based on a quantity of documents for that subject assigned to the first group of documents relative to a total quantity of documents for that subject and ranks that subject based on the determined score for each subject.
Public/Granted literature
- US20180365589A1 MACHINE LEARNING FOR RANKING CANDIDATE SUBJECTS BASED ON A TRAINING SET Public/Granted day:2018-12-20
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