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Clustering XML Documents using Structural Similarity
http://hdl.handle.net/20.500.12678/0000004985
http://hdl.handle.net/20.500.12678/00000049850948d3ee-fade-4475-99f5-2dd471f97d45
4856f978-2b46-4f22-abc9-f7cf77f3400e
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psc2010paper (150).pdf (145 Kb)
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Article | ||||||
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Publication | ||||||
Title | ||||||
Title | Clustering XML Documents using Structural Similarity | |||||
Language | en | |||||
Publication date | 2010-12-16 | |||||
Authors | ||||||
Lwin, Moet Moet | ||||||
Htoon, Ei Chaw | ||||||
Description | ||||||
Extensible Mark-up Language (XML) isincreasingly important in data exchange andinformation management. The automatic processingand management of XML-based data are ever morepopular research issues due to the increasingabundant use of XML, especially on the web.Clustering is also helpful for categorizing webdocuments. Clustering, which means the physicalarrangement of objects, can be an important factor inimproving the performance in the storage model.Clustering XML documents using structuralsimilarity based on Progressively Clustering XML byStructural Similarity (PCXSS) method is presented inthis paper. The PCXSS method intends to deal withthe heterogeneous XML schemas to cluster XMLdocuments by considering only the structuralsimilarity. The efficiency of PCXSS methodology hasbeen analysed with the real datasets which are ACMSIGMOD record, DBLP, XML Repository andWisconsin’s XML data bank. | ||||||
Keywords | ||||||
Clustering, PCXSS Methodology | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/882 | |||||
Journal articles | ||||||
Fifth Local Conference on Parallel and Soft Computing | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |