Title :
Next-Item Discovery in the Market Basket Analysis
Author_Institution :
ESCS, Polytech. Inst. of Lisboa
Abstract :
This paper addresses the problem of finding the next-item for each customer in large database marketing and can be seem as an extension of the market basket analysis. Most of the existing software uses Apriori-like algorithms. The outputs of the Apriori algorithms are easy to understand and many new patterns can be identified. However, the sheer number of association rules may make the interpretation of the results difficult. The aim of this work is to automate the cross-selling strategy. We would like to simplify the work of the marketer, avoiding the analysis of thousands of rules in associating customers with their next-item
Keywords :
data mining; marketing data processing; Apriori-like algorithms; association rules; cross-selling strategy; database marketing; market basket analysis; next-item discovery; Association rules; Banking; Customer profiles; Data mining; IEEE members; Insurance; Internet; Itemsets; Software algorithms; Transaction databases; database marketing; market basket analysis; temporal knowledge extraction;
Conference_Titel :
Artificial intelligence, 2005. epia 2005. portuguese conference on
Conference_Location :
Covilha
Print_ISBN :
0-7803-9366-X
Electronic_ISBN :
0-7803-9366-X
DOI :
10.1109/EPIA.2005.341294