Abstract
Clustering XML documents semantically has become a major challenge in XML data managements. The key research issue is to find the similarity functions of XML documents. However, previous work gave more importance to the topology structure than to the semantic information. In this paper, the computation of similarity between two XML documents is based on both structural and semantic information. Then a minimal spanning tree clustering method is used to cluster XML documents. The experiment results show that the new method performs better than baseline similarity measure in terms of purity and rand index.
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Song, L., Ma, J., Lei, J., Zhang, D., Wang, Z. (2009). Semantic Structural Similarity Measure for Clustering XML Documents. In: Liu, W., Luo, X., Wang, F.L., Lei, J. (eds) Web Information Systems and Mining. WISM 2009. Lecture Notes in Computer Science, vol 5854. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05250-7_25
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DOI: https://doi.org/10.1007/978-3-642-05250-7_25
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