Re-Mining Association Mining Results through Visualization, Data Envelopment Analysis, and Decision Trees

Node size denotes the item’s minimum price, and the node color denotes the item’s PercOfPositiveAssoc value. The highlighted item triggers the sales of many items and also brings more revenue itself.
Node size denotes the item’s minimum price, and the node color denotes the item’s PercOfPositiveAssoc value. The highlighted item triggers the sales of many items and also brings more revenue itself.

Re-mining is a general framework which suggests the execution of additional data mining steps based on the results of an original data mining process. This study investigates the multi-faceted re-mining of association mining results, develops and presents a practical methodology, and shows the applicability of the developed methodology through real world data. The methodology suggests re-mining using data visualization, data envelopment analysis, and decision trees. Six hypotheses, regarding how re-mining can be carried out on association mining results, are answered in the case study through empirical analysis.

Ertek, G., Tunç, M.M., (2012) “Re-Mining Association Mining Results through Visualization, Data Envelopment Analysis, and Decision Trees”, in Computational Intelligence Applications in Industrial Engineering, Ed: C. Kahraman, Springer.

Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.

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Re-mining Association Mining Results Through Visualization, Data Envelopment Analysis, And Decision Trees

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