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http://dx.doi.org/10.3745/KIPSTD.2010.17D.1.001

Utilizing the Effect of Market Basket Size for Improving the Practicality of Association Rule Measures  

Kim, Won-Seo (국민대학교 비즈니스IT전문대학원)
Jeong, Seung-Ryul (국민대학교 비즈니스IT전문대학원)
Kim, Nam-Gyu (국민대학교 비즈니스IT전문대학원)
Publication Information
The KIPS Transactions:PartD / v.17D, no.1, 2010 , pp. 1-8 More about this Journal
Abstract
Association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from voluminous transactional data. Certainly, one of the major purposes of association rule mining is utilizing the acquired knowledge to provide marketing strategies such as catalogue design, cross-selling and shop allocation. However, this requires too much time and high cost to only extract the actionable and profitable knowledge from tremendous numbers of discovered patterns. In currently available literature, a number of interest measures have been devised to accelerate and systematize the process of pattern evaluation. Unfortunately, most of such measures, including support and confidence, are prone to yielding impractical results because they are calculated only from the sales frequencies of items. For instance, traditional measures cannot differentiate between the purchases in a small basket and those in a large shopping cart. Therefore, some adjustment should be made to the size of market baskets because there is a strong possibility that mutually irrelevant items could appear together in a large shopping cart. Contrary to the previous approaches, we attempted to consider market basket's size in calculating interest measures. Because the devised measure assigns different weights to individual purchases according to their basket sizes, we expect that the measure can minimize distortion of results caused by accidental patterns. Additionally, we performed intensive computer simulations under various environments, and we performed real case analyses to analyze the correctness and consistency of the devised measure.
Keywords
Association Rule Mining; Data Mining; Market Basket Analysis; Interest Measures;
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Times Cited By KSCI : 3  (Citation Analysis)
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