Abstract
Market basket analysis has been an elementary part of quantitative decision support in retail marketing for many years and it is regularly cited as a prime application area of data mining. In this paper two competitive neural network approaches are presented and discussed with respect to their suitability for purchase interdependence analysis on the product category level. Particular attention is paid to the user-oriented representation or visualisation of cross-category dependences. Both approaches are applied to point of sales scanner data provided by a German retail chain to check how far they are able to uncover presumed purchase interdependences.
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