Invention Grant
US07672865B2 Method and apparatus for retail data mining using pair-wise co-occurrence consistency
有权
零售数据挖掘的方法和装置,使用成对的同现一致性
- Patent Title: Method and apparatus for retail data mining using pair-wise co-occurrence consistency
- Patent Title (中): 零售数据挖掘的方法和装置,使用成对的同现一致性
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Application No.: US11256386Application Date: 2005-10-21
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Publication No.: US07672865B2Publication Date: 2010-03-02
- Inventor: Shailesh Kumar , Edmond D. Chow , Michinari Momma
- Applicant: Shailesh Kumar , Edmond D. Chow , Michinari Momma
- Applicant Address: US MN Minneapolis
- Assignee: Fair Isaac Corporation
- Current Assignee: Fair Isaac Corporation
- Current Assignee Address: US MN Minneapolis
- Agency: Mintz, Levin, Cohn, Ferris, Glovsky and Popeo, P.C.
- Main IPC: G06F17/30
- IPC: G06F17/30

Abstract:
The invention, referred to herein as PeaCoCk, uses a unique blend of technologies from statistics, information theory, and graph theory to quantify and discover patterns in relationships between entities, such as products and customers, as evidenced by purchase behavior. In contrast to traditional purchase-frequency based market basket analysis techniques, such as association rules which mostly generate obvious and spurious associations, PeaCoCk employs information-theoretic notions of consistency and similarity, which allows robust statistical analysis of the true, statistically significant, and logical associations between products. Therefore, PeaCoCk lends itself to reliable, robust predictive analytics based on purchase-behavior.
Public/Granted literature
- US20070100680A1 Method and apparatus for retail data mining using pair-wise co-occurrence consistency Public/Granted day:2007-05-03
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