XML documents clustering using Tensor Space Model

Kutty, Sangeetha, Nayak, Richi, & Li, Yuefeng (2011) XML documents clustering using Tensor Space Model. In Proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Springer, InterContinental Shenzhen, Shenzhen.

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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.

Impact and interest:

3 citations in Web of Science®
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243 since deposited on 18 May 2011
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ID Code: 41717
Item Type: Conference Paper
Refereed: Yes
Keywords: Tensor, XML, Clustering, Decomposition, Wikipedia
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > INFORMATION SYSTEMS (080600)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2011 Springer
Copyright Statement: The original publication is available at SpringerLink
Deposited On: 18 May 2011 21:32
Last Modified: 22 Jun 2017 14:43

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