Re-mining item associations: Methodology and a case study in apparel retailing
Association mining is the conventional data mining technique for analyzing market basket data and it reveals the positive and negative associations between items. While being an integral part of transaction data, pricing and time information have not been integrated into market basket analysis in earlier studies. This paper proposes a new approach to mine price, time and domain related attributes through re-mining of association mining results. The underlying factors behind positive and negative relationships can be characterized and described through this second data mining stage. The applicability of the methodology is demonstrated through the analysis of data coming from a large apparel retail chain, and its algorithmic complexity is analyzed in comparison to the existing techniques.
Demiriz, A., Ertek, G., Kula, U., Atan, T. (2011). “Re-Mining Item Associations: Methodology and a Case Study in Apparel Retailing”. Decision Support Systems, 52,pp. 284–293.
Note: This is the final draft version of this paper. Please cite this paper (or this final draft) as above.
Dr. Gürdal Ertek @ Social Web:
You may be interested
Wind Turbine Accidents: A Data Mining StudyDr. Gurdal Ertek - December 12, 2016
Fig. 1. The cause-effect relationship and stages where an accident occurs. Wind Turbine Accidents: A Data Mining Study While the…
Perception gap and its impact on supply chain performanceDr. Gurdal Ertek - January 10, 2016
[caption id="attachment_571" align="alignnone" width="843"] Figure 4. SEM modelling for relationship between performance gaps and performance shortfall[/caption] Figure 4. SEM modelling…
New knowledge in strategic management through visually mining semantic networksDr. Gurdal Ertek - January 10, 2016
Fig. 5. Outlier objects. New knowledge in strategic management through visually mining semantic networks Today’s highly competitive business world requires…