A Data Mining Approach for Query Refinement

We propose a data mining approach for query refinement using Association Rules (ARs) among keywords being extracted from a document database. We are concerned with two issues in this paper. First, instead of using minimum support and minimum confidence which has little effectiveness of screening documents, we use maximum support and maximum confidence. Second, to further reduce the number of rules, we introduce two co-related concepts: “stem rule” and “coverage” The effectiveness of using ARs to screen is reported as well.