Semantic structural similarity for clustering XML documents

초록

The amount of XML documents is increasing rapidly. In order to analyze the information represented in XML documents efficiently, researches on XML document clustering are actively in progress. The key issue is how to devise the similarity measure between XML documents to be used for clustering. Since XML documents have hierarchical structure, it is not appropriate to cluster them by using a general document similarity measure. Previous works on similarity measure for XML document clustering have no consideration for the semantic information as they consider only the structural information. In this paper, we propose the novel similarity measure that concurrently considers both structural and semantic information of XML document. Our experiments show that the proposed method improve accuracy on the clustering from the semantic point of view, compared to the previous works. ? 2008 IEEE.