Invention Grant
- Patent Title: Regularized model adaptation for in-session recommendations
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Application No.: US14864499Application Date: 2015-09-24
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Publication No.: US10586167B2Publication Date: 2020-03-10
- Inventor: Xu Miao , Yitong Zhou , Joel D. Young , Lijun Tang , Anmol Bhasin
- Applicant: LinkedIn Corporation
- Applicant Address: US WA Redmond
- Assignee: Microsoft Technology Licensing, LLC
- Current Assignee: Microsoft Technology Licensing, LLC
- Current Assignee Address: US WA Redmond
- Agency: Park, Vaughan, Fleming & Dowler LLP
- Agent Chia-Hsin Suen
- Main IPC: G06N20/00
- IPC: G06N20/00 ; G06Q10/00 ; G06Q30/02 ; G06Q10/06 ; G06N20/20

Abstract:
The disclosed embodiments provide a method and system for performing regularized model adaptation for in-session recommendations. During operation, the system obtains, from a server, a first global version of a statistical model. During a first user session with a user, the system improves a performance of the statistical model by using the first global version to output one or more recommendations to the user and using the first global version and user feedback from the user to create a first personalized version of the statistical model. At an end of the first user session, the system transmits an update containing a difference between the first personalized version and the first global version to the server for use in producing a second global version of the statistical model by the server.
Public/Granted literature
- US20170091652A1 REGULARIZED MODEL ADAPTATION FOR IN-SESSION RECOMMENDATIONS Public/Granted day:2017-03-30
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