Invention Grant
- Patent Title: Transfer model learning for relevance models
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Application No.: US16557263Application Date: 2019-08-30
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Publication No.: US11423104B2Publication Date: 2022-08-23
- Inventor: Manas Haribhai Somaiya , Mohit Rajkumar Kothari , Ian Robert Ackerman , Yuan Shao
- 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: G06F16/9535
- IPC: G06F16/9535 ; G06F16/957 ; G06N3/08 ; G06F16/9538 ; G06N20/00 ; G06F16/9536

Abstract:
Systems and techniques for a transfer model learning for relevance models are described herein. In an example, a system for member relevance prediction is adapted to collect a first data set of member interactions with the online service that occur on a first platform and train a first model using the first data set. The system for member relevance prediction may collect a second data set of member interactions with the online service that occur on a second platform. The system for member relevance prediction may predict a third data set related to member interactions using the first model and aggregate the first data set, the second data set, and the third data set. The system for member relevance prediction may train a second model for the second platform using the aggregated platform data and predict for the second platform, using the second model, online service items for the member.
Public/Granted literature
- US20210064682A1 TRANSFER MODEL LEARNING FOR RELEVANCE MODELS Public/Granted day:2021-03-04
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