- 专利标题： Hypergraph structure and truncation method that reduces computer processor execution time in predicting product returns based on large scale data
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申请号： US16194970申请日： 2018-11-19
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公开(公告)号： US11164229B2公开(公告)日： 2021-11-02
- 发明人: Yada Zhu , Ajay Ashok Deshpande , Jae-Eun Park , Anna Wanda Topol , Xuan Liu
- 申请人： International Business Machines Corporation
- 申请人地址： US NY Armonk
- 专利权人： International Business Machines Corporation
- 当前专利权人： International Business Machines Corporation
- 当前专利权人地址： US NY Armonk
- 代理机构： Scully, Scott, Murphy & Presser, P.C.
- 代理商 Daniel P. Morris
- 主分类号： G06Q30/02
- IPC分类号： G06Q30/02 ; G06Q30/06
摘要：
A hypergraph is constructed based on historical shopping cart data. A node of the hypergraph corresponds to a shopping basket, and a hyperedge of the hypergraph corresponds to a unique product, the hyperedge connecting all nodes of the hypergraph representing baskets containing the unique product. A hypergraph partition algorithm identifies a cluster of shopping baskets represented in the hypergraph and determined to be similar to a given basket. Based on the cluster of shopping baskets a dual-level return prediction is performed. The dual-level return prediction includes predicting whether the given basket will be returned, and based on predicting that the given basket will be returned, predicting a probability that a product in the given basket will be returned. Based on predicting that the given basket will be returned, an ameliorative action is performed to reduce the probability.
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