Abstract
There exist several methods to measuring the structural similarity among XML documents. The data mining approach seems to be a novel, interesting and promising one. In view of the deficiencies encountered by ignoring the hierarchical information in encoding the paths for mining, we propose a new sequential pattern mining scheme for XML document similarity computation. It makes use of the hierarchical information to computing the document structural similarity. In addition, it includes a post-processing step to reuse the mined patterns to estimate the similarity of unmatched elements so that another metric to qualify the similarity between XML documents can be introduced. Encouraging experimental results were obtained and reported.
This work was supported by the research project H-ZJ84 and the full version of this paper can be found in http://www.comp.polyu.edu.hk/~cskchung/Paper/PAKDD03.pdf
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Leung, Hp., Chung, Fl., Chan, S.Cf. (2003). A New Sequential Mining Approach to XML Document Similarity Computation. In: Whang, KY., Jeon, J., Shim, K., Srivastava, J. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2003. Lecture Notes in Computer Science(), vol 2637. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36175-8_35
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DOI: https://doi.org/10.1007/3-540-36175-8_35
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