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.
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Wang, T., Liu, DX., Lin, XZ., Sun, W., Ahmad, G. (2006). Clustering Large Scale of XML Documents. In: Chung, YC., Moreira, J.E. (eds) Advances in Grid and Pervasive Computing. GPC 2006. Lecture Notes in Computer Science, vol 3947. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11745693_44
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DOI: https://doi.org/10.1007/11745693_44
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33809-3
Online ISBN: 978-3-540-33810-9
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