Abstract
We present a novel clustering algorithm to group the XML documents by similar structures. We introduce a Level structure format to represent the XML documents for efficient processing. We develop a global criterion function that do not require the pair-wise similarity to be computed between two individual documents, rather measures the similarity at clustering level utilising structural information of the XML documents. The experimental analysis shows the method to be fast and accurate.
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© 2006 Springer-Verlag Berlin Heidelberg
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Nayak, R., Xu, S. (2006). XCLS: A Fast and Effective Clustering Algorithm for Heterogenous XML Documents. In: Ng, WK., Kitsuregawa, M., Li, J., Chang, K. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2006. Lecture Notes in Computer Science(), vol 3918. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11731139_35
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DOI: https://doi.org/10.1007/11731139_35
Publisher Name: Springer, Berlin, Heidelberg
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