Abstract
Mining association rules is well established in quantitative business research literature and makes up an up-and-coming topic in marketing practice. However, reducing the analysis to the assessment and interpretation of a few selected rules does not provide a complete picture of the data structure revealed by the rules.
This paper introduces a new approach of visualizing relations between items by assigning them to a rectangular grid with respect to their mutual association. The visualization task leads to a quadratic assignment problem and is tackled by means of a genetic algorithm. The methodology is demonstrated by evaluating a set of rules describing marketing practices in Russia.
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BLUM, C. and ROLI, A. (2003): Metaheuristics in Combinatorial Optimazation: Overview and Conceptual Comparision, ACM Computing Survey, 35/3, 268–308.
CELA, E. (1997):The Quadratic Assignment Problem: Theory and Algorithms, Kluwer, Dordrecht.
HILDERMAN, R.J. and HAMILTON H.J. (2001): Evaluation of Interestingness Measures for Ranking Discovered Knowledge. In: D. Cheung, G.J. Williams, and Q. Li (Eds.): Advances in Knowledge Discovery and DataMining, Springer, Berlin, 247–259.
SAHNI, S.K. and GRONZALEZ, T. (1976):P-Complete Approximation Problems, Journal of Association of Computing Machinery, 23/3, 555–565.
WAGNER, R. (2005a): Mining Promising Qualification Patterns. In: D. Baier and K.-D. Wernecke (Eds.): Innovations in Classification, Data Science, and Information Systems. Springer, Berlin, 249–256.
WAGNER, R. (2005b): Contemporary Marketing Practices in Russia, European Journal of Marketing, Vol. 39/1–2, 199–215.
ZAKI, M.J. and OGIHARA, M. (1998): Theoretical Foundations of Association Rules. In: Proceedings of 3rd ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery.
ZBIGNIEW, M. and FOGEL, D.B. (2000): How to Solve it: Modern Heuristics, Springer, Berlin.
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Wagner, R. (2006). Patterns of Associations in Finite Sets of Items. In: Batagelj, V., Bock, HH., Ferligoj, A., Žiberna, A. (eds) Data Science and Classification. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg . https://doi.org/10.1007/3-540-34416-0_30
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DOI: https://doi.org/10.1007/3-540-34416-0_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34415-5
Online ISBN: 978-3-540-34416-2
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