As XML prevails over the Internet, the efficient retrieval of XML data becomes important. Research to improve query response times has been largely concentrated on indexing XML documents and processing regular path expressions. Another approach is to discover frequent query patterns since the answers to these queries can be stored and indexed. Mining frequent query patterns requires more than simple tree matching since the XML queries involves special characters such as "*" or "//". In

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... the matching process can be expensive since the search space is exponential to the size of XML schema. In this paper, we present two mining algorithms, XQPMiner and XQPMinerTID, to discover frequent query pattern trees from a large collection of XML queries efficiently. Both algorithms exploit schema information to guide the enumeration of candidate subtrees, thus eliminating unnecessary node expansions. Experiments results show that the proposed methods are efficient and have good scalability.