Invention Grant
- Patent Title: Search optimization based on relevant-parameter selection
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Application No.: US16553375Application Date: 2019-08-28
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Publication No.: US11238124B2Publication Date: 2022-02-01
- Inventor: Huichao Xue
- Applicant: Microsoft Technology Licensing, LLC
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Agency: Schwegman Lundberg & Woessner, P.A.
- Main IPC: G06F7/02
- IPC: G06F7/02 ; G06F16/00 ; G06F16/9538 ; G06N20/20 ; G06F16/9035 ; G06F16/9535

Abstract:
Methods, systems, and computer programs are presented for search optimization based on relevant-parameter selection. One method includes an operation for training a machine-learning program with information about users of an online service to generate a machine-learning model that calculates parameter preference scores for a plurality of parameters. Further, the method includes operations for detecting a job search for a user, identifying user parameters associated with the user, and calculating, by the machine-learning model, the parameter preference scores for the user parameters. Further, search parameters are determined by selecting a predetermined number of user parameters base on the parameter preference scores. A search of a job-postings database is performed with the search parameters, and the results are presented on a display.
Public/Granted literature
- US20210064684A1 SEARCH OPTIMIZATION BASED ON RELEVANT-PARAMETER SELECTION Public/Granted day:2021-03-04
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