Abstract
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.
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Hou, J., Nayak, R. (2013). The Heterogeneous Cluster Ensemble Method Using Hubness for Clustering Text Documents. In: Lin, X., Manolopoulos, Y., Srivastava, D., Huang, G. (eds) Web Information Systems Engineering – WISE 2013. WISE 2013. Lecture Notes in Computer Science, vol 8180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41230-1_9
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DOI: https://doi.org/10.1007/978-3-642-41230-1_9
Publisher Name: Springer, Berlin, Heidelberg
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