XML documents cluster research based on frequent subpatterns

Tienan Ding; Wei Li; Xiongfei Li

doi:10.1117/12.2203249

3 December 2015 XML documents cluster research based on frequent subpatterns

Tienan Ding, Wei Li, Xiongfei Li

Proceedings Volume 9794, Sixth International Conference on Electronics and Information Engineering; 97943A (2015) https://doi.org/10.1117/12.2203249
Event: Sixth International Conference on Electronics and Information Engineering, 2015, Dalian, China

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.

Citation Download Citation

Tienan Ding, Wei Li, and Xiongfei Li "XML documents cluster research based on frequent subpatterns", Proc. SPIE 9794, Sixth International Conference on Electronics and Information Engineering, 97943A (3 December 2015); https://doi.org/10.1117/12.2203249

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