Goodman-Kruskal measure associated clustering for categorical data

Wenxue Huang, Yuanyi Pan and Jianhong Wu

International Journal of Data Mining, Modelling and Management, 2012, vol. 4, issue 4, 334-360

Abstract: Motivated by business interest of return on investment (ROI) in marketing, we develop a conceptual clustering algorithm for categorical data with a response variable based on a variation to Goodman-Kruskal measure. The key to this algorithm is an implicitly cost-effective dissimilarity measure derived from a probabilistic association rule between the response and the explanatory scenarios. Applications to a real dataset FAMEX96 illustrate how useful information can be mined from marketing data using this dissimilarity measure.

Keywords: categorical data; supervised clustering; dissimilarity measures; decisive rules; Goodman-Kruskal measure; return on investment; ROI; scenario association; target variable; clustering algorithms; marketing data; data mining. (search for similar items in EconPapers)
Date: 2012
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