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Clustering and Classification in Text Collections Using Graph Modularity

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Preprint
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Submission Date
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arXiv ID: 1105.5789
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arXiv
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Abstract

A new fast algorithm for clustering and classification of large collections of text documents is introduced. The new algorithm employs the bipartite graph that realizes the word-document matrix of the collection. Namely, the modularity of the bipartite graph is used as the optimization functional. Experiments performed with the new algorithm on a number of text collections had shown a competitive quality of the clustering (classification), and a record-breaking speed.

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