- 专利标题: Method and system for making recommendations from binary data using neighbor-score matrix and latent factors
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申请号: US14975872申请日: 2015-12-21
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公开(公告)号: US10932003B2公开(公告)日: 2021-02-23
- 发明人: Maksims Volkovs , Tomi Poutanen
- 申请人: THE TORONTO-DOMINION BANK
- 申请人地址: CA Toronto
- 专利权人: THE TORONTO-DOMINION BANK
- 当前专利权人: THE TORONTO-DOMINION BANK
- 当前专利权人地址: CA Toronto
- 代理机构: Fenwick & West LLP
- 主分类号: G06F15/18
- IPC分类号: G06F15/18 ; H04N21/466 ; H04N21/81 ; G06Q30/06 ; G06Q30/02 ; G06F16/9535
摘要:
One embodiment is a method executed by a computer system that applies collaborative filtering to provide a recommendation to a user. The method includes retrieving a binary matrix that includes rows and columns of binary data for preferences of users on items; applying a neighborhood-based approach to convert the binary matrix into a neighbor-score matrix; applying a factorization to approximate the neighbor-score matrix with a product of lower rank matrices; calculating a user factor and an item factor based on the factorization; calculating scores for user-item pairs by computing a dot product between the user factor and the item factor; sorting the scores of the user-item pairs to generate the recommendation to the user; and providing the recommendation to a general-purpose computer of the user.
公开/授权文献
- US20160217374A1 METHOD AND SYSTEM UTILIZING COLLABORATIVE FILTERING 公开/授权日:2016-07-28
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