A study on answering a data mining query using a materialized view

Abstract. One of the classic data mining problems is discovery of frequent itemsets. This problem particularly attracts database community as it resembles traditional database querying. In this paper we consider a data mining system which supports storing of previous query results in the form of materialized data mining views. While numerous works have shown that reusing results of previous frequent itemset queries can significantly improve performance of data mining query processing, a thorough study of possible differences between the current query and a materialized view has not been presented yet. In this paper we classify possible differences into six classes, provide I/O cost analysis for all the classes, and experimentally evaluate the most promising ones.