Market Basket Analysis with Neural Gas Networks and Self-organising Maps

Decker R, Monien K (2003)
Journal of Targeting, Measurement and Analysis for Marketing 11(4): 373-386.

Journal Article | Published | English

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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 visualization 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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Decker R, Monien K. Market Basket Analysis with Neural Gas Networks and Self-organising Maps. Journal of Targeting, Measurement and Analysis for Marketing. 2003;11(4):373-386.
Decker, R., & Monien, K. (2003). Market Basket Analysis with Neural Gas Networks and Self-organising Maps. Journal of Targeting, Measurement and Analysis for Marketing, 11(4), 373-386.
Decker, R., and Monien, K. (2003). Market Basket Analysis with Neural Gas Networks and Self-organising Maps. Journal of Targeting, Measurement and Analysis for Marketing 11, 373-386.
Decker, R., & Monien, K., 2003. Market Basket Analysis with Neural Gas Networks and Self-organising Maps. Journal of Targeting, Measurement and Analysis for Marketing, 11(4), p 373-386.
R. Decker and K. Monien, “Market Basket Analysis with Neural Gas Networks and Self-organising Maps”, Journal of Targeting, Measurement and Analysis for Marketing, vol. 11, 2003, pp. 373-386.
Decker, R., Monien, K.: Market Basket Analysis with Neural Gas Networks and Self-organising Maps. Journal of Targeting, Measurement and Analysis for Marketing. 11, 373-386 (2003).
Decker, Reinhold, and Monien, K. “Market Basket Analysis with Neural Gas Networks and Self-organising Maps”. Journal of Targeting, Measurement and Analysis for Marketing 11.4 (2003): 373-386.
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