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A Clustering Technique using Common Structures of XML Documents  

Hwang, Jeong-Hee (충북대학교 컴퓨터과학과)
Ryu, Keun-Ho (충북대학교 전기전자컴퓨터공학부)
Publication Information
Journal of KIISE:Databases / v.32, no.6, 2005 , pp. 650-661 More about this Journal
Abstract
As the Internet is growing, the use of XML which is a standard of semi-structured document is increasing. Therefore, there are on going works about integration and retrieval of XML documents. However, the basis of efficient integration and retrieval of documents is to cluster XML documents with similar structure. The conventional XML clustering approaches use the hierarchical clustering algorithm that produces the demanded number of clusters through repeated merge, but it have some problems that it is difficult to compute the similarity between XML documents and it costs much time to compare similarity repeatedly. In order to address this problem, we use clustering algorithm for transactional data that is scale for large size of data. In this paper we use common structures from XML documents that don't have DTD or schema. In order to use common structures of XML document, we extract representative structures by decomposing the structure from a tree model expressing the XML document, and we perform clustering with the extracted structure. Besides, we show efficiency of proposed method by comparing and analyzing with the previous method.
Keywords
Document Clustering; XML Clustering; XML Document; Structural Similarity;
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