@inproceedings{945a3f1fc05447a781e0fb81df728675,
title = "Multilevel conditional fuzzy C-means clustering of XML documents",
abstract = "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.",
keywords = "Clustering, Clustering XML documents",
author = "Michal Kozielski",
year = "2007",
month = aug,
day = "31",
doi = "10.1007/978-3-540-74976-9\_55",
language = "English",
isbn = "9783540749752",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "532--539",
booktitle = "Knowledge Discovery in Database",
address = "Germany",
note = "11th European Conference on Principles and Practice of Knowledge Discovery in Databases, PKDD 2007 ; Conference date: 17-09-2007 Through 21-09-2007",
}