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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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
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