Abstract
XML becomes increasingly important in data exchange and information management. Starting point for retrieving the information and integrating the documents efficiently is clustering the documents that have similar structure. Thus, in this paper, we propose a new XML document clustering method based on similar structure. Our approach first extracts the representative structures of XML documents by sequential pattern mining. And then we cluster XML documents of similar structure using the clustering algorithm for transactional data, assuming that an XML document as a transaction and the frequent structure of documents as the items of the transaction. We also apply our technique to XML retrieval. Our experiments show the efficiency and good performance of the proposed clustering method.
This work was supported by University IT Research Center Project and ETRI in Korea.
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Hwang, J.H., Ryu, K.H. (2004). A New XML Clustering for Structural Retrieval. In: Atzeni, P., Chu, W., Lu, H., Zhou, S., Ling, TW. (eds) Conceptual Modeling – ER 2004. ER 2004. Lecture Notes in Computer Science, vol 3288. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30464-7_30
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DOI: https://doi.org/10.1007/978-3-540-30464-7_30
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23723-5
Online ISBN: 978-3-540-30464-7
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