Knowledge discovery process from databases has gained importance recently. Finding and using the valuable and meaningful data which is hidden in large databases can have strategic importance for the organizations to gain competitive advantage. In this context, data mining methods are used to analyze customer purchasing data which is called “market basket analysis”. This analysis provides insight into the combination of products within a customer’s ‘basket’. In this study, a market basket analysis is conducted to identify a customer purchasing behaviour with Formal Concept Analysis (FCA). The FCA technique is one of the data mining methods using formal contexts and concept lattices. So, this method provides to create association rules based on lattices reflecting the relationships among the attributes in a database.
CITATION STYLE
Üstündağ, A., & Bal, M. (2014). Evaluating market basket data with formal concept analysis. In Springer Proceedings in Complexity (pp. 113–118). Springer. https://doi.org/10.1007/978-94-007-7362-2_15
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