Efficient extraction of maximally common subtrees from XML documents for web services

Web services need to integrate and classify XML documents received from multiple and heterogeneous sources. To this end, it requires a mechanism for extracting common structures from a large XML dataset, called frequent subtrees. In this paper we propose an efficient and scalable algorithm, EMaxS, for mining frequent subtrees of Web XML documents stored in Web servers. Compared with previous works, the proposed algorithm uses only simple bitwise operations and does not require any join steps, which are typically expensive