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A Progressive Clustering Algorithm to Group the XML Data by Structural and Semantic Similarity

Nayak, Richi & Tran, Tien (2007) A Progressive Clustering Algorithm to Group the XML Data by Structural and Semantic Similarity. International Journal of Pattern Recognition and Artificial Intelligence, 21(4), pp. 723-743.

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Abstract

Since the emergence in the popularity of XML for data representation and exchange over the Web, the distribution of XML documents has rapidly increased. It has become a challenge for researchers to turn these documents into a more useful information utility. In this paper, we introduce a novel clustering algorithm PCXSS that keeps the heterogeneous XML documents into various groups according to their similar structural and semantic representations. We develop a global criterion function CPSim that progressively measures the similarity between a XML document and existing clusters, ignoring the need to compute the similarity between two individual documents. The experimental analysis shows the method to be fast and accurate.

Impact and interest:

16 citations in Scopus
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9 citations in Web of Science®

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Full-text downloads:

296 since deposited on 08 Jul 2008
172 in the past twelve months

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ID Code: 13996
Item Type: Journal Article
Additional Information: For more information, please refer to the journal's website (see hypertext link) or contact the author.
DOI: 10.1142/S0218001407005648
ISSN: 1793-6381
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > LIBRARY AND INFORMATION STUDIES (080700) > Information Retrieval and Web Search (080704)
Divisions: Past > Schools > Computer Science
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2007 World Scientific Publishing
Deposited On: 08 Jul 2008
Last Modified: 01 Mar 2012 10:30

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