Title :
XML Documents Clustering Using Tensor Space Model -- A Preliminary Study
Author :
Kutty, Sangeetha ; Nayak, Richi ; Li, Yuefeng
Author_Institution :
Sch. of Comput. Sci., Queensland Univ. of Technol. (QUT), Brisbane, QLD, Australia
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.
Keywords :
XML; matrix decomposition; pattern clustering; tensors; vectors; XML documents clustering; matrix factorisation; tensor space model; vector space model; Clustering; Decomposition; Structure and Content; Tensor; XML documents;
Conference_Titel :
Data Mining Workshops (ICDMW), 2010 IEEE International Conference on
Conference_Location :
Sydney, NSW
Print_ISBN :
978-1-4244-9244-2
Electronic_ISBN :
978-0-7695-4257-7
DOI :
10.1109/ICDMW.2010.106
