- Patent Title: Document ranking by contextual vectors from natural language query
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Application No.: US15691956Application Date: 2017-08-31
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Publication No.: US10592542B2Publication Date: 2020-03-17
- Inventor: Takashi Fukuda , Hiroaki Kikuchi
- 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: Garg Law Firm, PLLC
- Agent Rakesh Garg; Reza Sarbakhsh
- Main IPC: G06F16/00
- IPC: G06F16/00 ; G06F16/33 ; G06F17/28 ; G06F16/242 ; G06F16/2457 ; G06F17/27

Abstract:
A set of keywords is extracted from a query. Natural Language Processing (NLP) is performed on the query to extract a set of contextual words for a keyword from the query. For the query, a first score of a first vector is computed, where the first vector represents a first contextual word. For a first result in a result set, a first result score of a first result vector is computed, where the first vector represents a first result contextual word in a set of result contextual words corresponding to the keyword in the first result. Using the first score and the first result score, a first similarity value is computed for the first result. The first result is re-ranked relative to a second result according to the first similarity value for the first result and a second similarity value for the second result in the result set.
Public/Granted literature
- US20190065505A1 DOCUMENT RANKING BY CONTEXTUAL VECTORS FROM NATURAL LANGUAGE QUERY Public/Granted day:2019-02-28
Information query