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.
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.
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|Item Type:||Journal Article|
|Additional Information:||For more information, please refer to the journal's website (see hypertext link) or contact the author.|
|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 00:30|
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