Clustering large scale of XML documents

Authors:
Tong Wang;Da-Xin Liu;Xuan-Zuo Lin;Wei Sun;Gufran Ahmad
Affiliations:
Department of Computer Science and Technology, Harbin Engineering University, China;Department of Computer Science and Technology, Harbin Engineering University, China;Northeast Agriculture University, Harbin, China;Department of Computer Science and Technology, Harbin Engineering University, China;Department of Computer Science and Technology, Harbin Engineering University, China
Venue:
GPC'06 Proceedings of the First international conference on Advances in Grid and Pervasive Computing
Year:
2006

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Abstract

Clustering is able to facilitate Information Retrieval. This paper addresses the issue of clustering a large number of XML documents. We propose ICX algorithm with a novel similarity metric based on quantitative path. In our approach, each document is firstly represented by path sequences extracted from XML trees. Then these sequences are mapped into quantitative path, by which the distance between documents can be computed with low complexity. Finally, the desired clusters are constructed by utilizing ICX method with literal local search. Experimental results, based on XML documents obtained from DBLP, show the effectiveness and good performance of the proposed techniques.