Method and apparatus for retail data mining using pair-wise co-occurrence consistency
US7672865B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 21, 2005 |
| Grant date | Mar 2, 2010 |
| Priority date | — |
| Expiry date | Nov 14, 2028 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q30/0605
- WIPO fieldIT methods for management
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.