XML documents clustering using a tensor space model

Authors:
Sangeetha Kutty;Richi Nayak;Yuefeng Li
Affiliations:
Faculty of Science and Technology, Queensland University of Technology, Brisbane, Australia;Faculty of Science and Technology, Queensland University of Technology, Brisbane, Australia;Faculty of Science and Technology, Queensland University of Technology, Brisbane, Australia
Venue:
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Year:
2011

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Abstract

The traditional Vector Space Model (VSM) is not able to represent both the structure and the content of XML documents. This paper introduces a novel method of representing XML documents in a Tensor Space Model (TSM) and then utilizing it for clustering. Empirical analysis shows that the proposed method is scalable for large-sized datasets; as well, the factorized matrices produced from the proposed method help to improve the quality of clusters through the enriched document representation of both structure and content information.