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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Multilevel Conditional Fuzzy C-Means Clustering of XML Documents
verfasst von : Michal Kozielski
Erschienen in: Knowledge Discovery in Databases: PKDD 2007
Verlag: Springer Berlin Heidelberg
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XML documents are the special kind of data having hierarchical structure. Typical clustering algorithms do not meet requirements which may be stated for analysis of such data. A novel, dedicated for XML documents clustering method called
Multilevel clustering of XML documents
(
ML
) is presented in the paper. The method clusters feature vectors encoding XML documents on the different structure levels. Application of
Conditional Fuzzy C-Means
algorithm to
ML
method is proposed in the paper and the advantage of this fuzzy method over hard approach to
ML
algorithm is discussed and proved. An application of
ML
method to accelerating query execution on XML documents is discussed in the paper. The experimental results performed on two data sets having different characteristics show that the proposed method of multilevel conditional fuzzy clustering of XML documents outperforms hard multilevel clustering.