NDLI: An Improved XML Document Clustering Using Path Feature

Content Provider	IEEE Xplore Digital Library
Author	Jin-sha Yuan Xin-ye Li Li-na Ma
Copyright Year	2008
Description	Author affiliation: Dept. of Electron. & Commun. Eng., North China Electr. Power Univ., Baoding (Jin-sha Yuan; Xin-ye Li; Li-na Ma)
Abstract	Extensible markup language (XML) documents clustering is useful to XML application such as XML search engine. The element tags and their position in the document's hierarchy provide valuable information to clustering XML documents. XML path can represent both element tags and their position information. Since common Xpath represents only parts of the XML structural, using common Xpath as XML structural representation is not always efficient to XML clustering, especially when those documents are with dissimilar structure. In this paper, we use all paths less than or equal to length L as feature vectors for XML documents. Since the feature vector matrix is usually sparse, we use bipartite graph to express association relation among XML documents and path features. Based on this idea, we improved the path-based XML clustering algorithm. Experiments are described to demonstrate its efficiency.
Starting Page	400
Ending Page	404
File Size	289893
Page Count	5
File Format	PDF
ISBN	9780769533056
DOI	10.1109/FSKD.2008.66
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Knowledge engineering Clustering methods Educational institutions Sparse matrices bipartite graph Tellurium path XML Search engines Bipartite graph XML clustering Fuzzy systems Power engineering and energy
Content Type	Text
Resource Type	Article

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