Patent: Retail Data Mining Using Co-Occurrence Consistency

The invention uses 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.

Method and apparatus for retail data mining using pair-wise co-occurrence consistency

United States Patent 7672865

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.

Inventors:

Kumar, Shailesh (San Diego, CA, US)
Chow, Edmond D. (Encinitas, CA, US)
Momma, Michinari (San Diego, CA, US)

Publication Date: 03/02/2010
Filing Date: 10/21/2005

Patent 7672865 PDF

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