Integration of deduction and induction for mining supermarket sale data

Datasift, a prototype system for the analysis of supermarket sales data based on data mining techniques, is presented. In market basket analysis, mining knowledge on customer behavior, which is actually useful to support marketing actions, is a difficult task, which requires non-trivial methods of employing and combining the data mining tools. To this purpose, we propose an architecture that integrates the deductive capabilities of a logic-based database language, LDL++, with the inductive capabilities of diverse data mining algorithms and tools, notably association rules. This paper presents an application of the integrated system to market basket analysis, and illustrates the high degree of expressiveness reached in dealing with high-level business rules.