We propose a cluster ensemble method to map the corpus documents into the semantic space embedded in Wikipedia and group them using multiple types of feature space. A heterogeneous cluster ensemble is constructed with multiple types of relations i.e. document-term, document-concept and document-category. A final clustering solution is obtained by exploiting associations between document pairs and hubness of the documents. Empirical analysis with various real data sets reveals that the proposed method outperforms state-of-the-art text clustering approaches. © 2013 Springer-Verlag.
CITATION STYLE
Hou, J., & Nayak, R. (2013). The heterogeneous cluster ensemble method using hubness for clustering text documents. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8180 LNCS, pp. 102–110). https://doi.org/10.1007/978-3-642-41230-1_9
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