Mining Positive and Negative Association Rules from XML Query Patterns for Caching

Recently, several approaches that mine frequent XML query patterns and cache their results have been proposed to improve query response time. However, frequent XML query patterns mined by these approaches ignore the temporal sequence between user queries. In this paper, we take into account the temporal features of user queries to discover association rules, which indicate that when a user inquires some information from the XML document, she/he will probably inquire some other information subsequently. We cluster XML queries according to their semantics first and then mine association rules between the clusters. Moreover, not only positive but also negative association rules are discovered to design the appropriate cache replacement strategy. The experimental results showed that our approach considerably improved the caching performance by significantly reducing the query response time.