Clustering transactions using large items
Proceedings of the eighth international conference on Information and knowledge management
Rule-assisted prefetching in Web-server caching
Proceedings of the ninth international conference on Information and knowledge management
Web log data warehousing and mining for intelligent web caching
Data & Knowledge Engineering - Building web warehouse
XCache: a semantic caching system for XML queries
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Mining Both Positive and Negative Association Rules
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
An Efficient and Scalable Algorithm for Clustering XML Documents by Structure
IEEE Transactions on Knowledge and Data Engineering
Efficient mining of XML query patterns for caching
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Improving XML Querying with Maximal Frequent Query Patterns
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part I: ICCS 2007
Bottom-up discovery of frequent rooted unordered subtrees
Information Sciences: an International Journal
BUXMiner: an efficient bottom-up approach to mining XML query patterns
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
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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.