Clustering and Classification in Text Collections Using Graph Modularity
Information Retrieval
2011-05-31 v1 Digital Libraries
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.
Cite
@article{arxiv.1105.5789,
title = {Clustering and Classification in Text Collections Using Graph Modularity},
author = {Grigory Pivovarov and Sergei Trunov},
journal= {arXiv preprint arXiv:1105.5789},
year = {2011}
}
Comments
11 pages, submitted to JMLR