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XCFS - a novel approach for clustering XML documents using both the structure and the content

Kutty, Sangeetha, Nayak, Richi, & Li, Yuefeng Y. (2009) XCFS - a novel approach for clustering XML documents using both the structure and the content. In Association for Computing Machinery, Asia World-Expo, Hong Kong.

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Abstract

XML document clustering is essential for many document handling applications such as information storage, retrieval, integration and transformation. An XML clustering algorithm should process both the structural and the content information of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. This paper introduces a novel approach that first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. The proposed method reduces the high dimensionality of input data by using only the structure-constrained content. The empirical analysis reveals that the proposed method can effectively cluster even very large XML datasets and outperform other existing methods.

Impact and interest:

2 citations in Scopus
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ID Code: 29655
Item Type: Conference Paper
Keywords: XML documents, Frequent mining, Clustering, Subtree mining, Structure and content
DOI: 10.1145/1645953.1646216
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Schools > School of Information Technology
Copyright Owner: Copyright 2009 [please consult the authors]
Deposited On: 14 Jan 2010 12:07
Last Modified: 01 Mar 2012 00:12

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