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XML documents clustering using tensor space model - A preliminary study

Kutty, Sangeetha, Nayak, Richi, & Li, Yuefeng (2010) XML documents clustering using tensor space model - A preliminary study. In 2010 IEEE International Conference on Data Mining Workshop (ICDMW), 13th December 2010, Sydney.

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Abstract

A hierarchical structure is used to represent the content of the semi-structured documents such as XML and XHTML. The traditional Vector Space Model (VSM) is not sufficient to represent both the structure and the content of such web documents. Hence in this paper, we introduce a novel method of representing the XML documents in Tensor Space Model (TSM) and then utilize it for clustering. Empirical analysis shows that the proposed method is scalable for a real-life dataset as well as the factorized matrices produced from the proposed method helps to improve the quality of clusters due to the enriched document representation with both the structure and the content information.

Impact and interest:

3 citations in Scopus
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ID Code: 40067
Item Type: Conference Paper
Keywords: XML documents, Clustering, Tensor, Structure and Content, Decomposition
DOI: 10.1109/ICDMW.2010.106
ISBN: 978-1-4244-9244-2
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Divisions: Past > Schools > Computer Science
Past > QUT Faculties & Divisions > Faculty of Science and Technology
Deposited On: 15 Feb 2011 12:41
Last Modified: 01 Mar 2012 11:40

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