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Proceedings Paper

XML documents cluster research based on frequent subpatterns
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Paper Abstract

XML data is widely used in the information exchange field of Internet, and XML document data clustering is the hot research topic. In the XML document clustering process, measure differences between two XML documents is time costly, and impact the efficiency of XML document clustering. This paper proposed an XML documents clustering method based on frequent patterns of XML document dataset, first proposed a coding tree structure for encoding the XML document, and translate frequent pattern mining from XML documents into frequent pattern mining from string. Further, using the cosine similarity calculation method and cohesive hierarchical clustering method for XML document dataset by frequent patterns. Because of frequent patterns are subsets of the original XML document data, so the time consumption of XML document similarity measure is reduced. The experiment runs on synthetic dataset and the real datasets, the experimental result shows that our method is efficient.

Paper Details

Date Published: 3 December 2015
PDF: 5 pages
Proc. SPIE 9794, Sixth International Conference on Electronics and Information Engineering, 97943A (3 December 2015); doi: 10.1117/12.2203249
Show Author Affiliations
Tienan Ding, Jilin Univ. (China)
Wei Li, Sichuan Normal Univ. (China)
Xiongfei Li, Jilin Univ. (China)

Published in SPIE Proceedings Vol. 9794:
Sixth International Conference on Electronics and Information Engineering
Qiang Zhang, Editor(s)

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