Invention Grant
- Patent Title: Latent user models for personalized ranking
- Patent Title (中): 潜在用户模型,用于个性化排名
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Application No.: US13517767Application Date: 2012-06-14
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Publication No.: US09477757B1Publication Date: 2016-10-25
- Inventor: Huazhong Ning , Zhen Li , Hrishikesh Aradhye
- Applicant: Huazhong Ning , Zhen Li , Hrishikesh Aradhye
- Applicant Address: US CA Mountain View
- Assignee: GOOGLE INC.
- Current Assignee: GOOGLE INC.
- Current Assignee Address: US CA Mountain View
- Agency: Lowenstein Sandler LLP
- Main IPC: G06F17/30
- IPC: G06F17/30

Abstract:
A method includes generating a ranking model and a baseline mixing weight for each latent user category from a plurality of latent user categories based on a community preference dataset and one or more latent variables that relate the users from the community of users to the latent user categories. The method also includes generating a personalized mixing weight for each latent user category for a specified user based on an individual preference dataset, the ranking models for the latent user category, and one or more latent variables that relate the specified user to the latent user categories. The method also includes adjusting the personalized mixing weight for each latent user category for the specified user based on the baseline mixing weights, and generating ranking output for at least some objects from the plurality of objects using the personalized mixing weights and the ranking models.
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