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Hybrid online non-negative matrix factorization for clustering of documents

Jadhao, Vinod and Murty, Narasimha M (2012) Hybrid online non-negative matrix factorization for clustering of documents. In: ICONIP 2012 19th International Conference, November 12-15, 2012, Doha, Qatar.

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Official URL: http://dx.doi.org/10.1007/978-3-642-34475-6_62


When document corpus is very large, we often need to reduce the number of features. But it is not possible to apply conventional Non-negative Matrix Factorization(NMF) on billion by million matrix as the matrix may not fit in memory. Here we present novel Online NMF algorithm. Using Online NMF, we reduced original high-dimensional space to low-dimensional space. Then we cluster all the documents in reduced dimension using k-means algorithm. We experimentally show that by processing small subsets of documents we will be able to achieve good performance. The method proposed outperforms existing algorithms.

Item Type: Conference Paper
Additional Information: Copyright of this article belongs to Springer Berlin Heidelberg.
Keywords: Non-Negative Matrix Factorization(NMF); Online NMF; Clustering
Department/Centre: Division of Electrical Sciences > Computer Science & Automation
Depositing User: Id for Latest eprints
Date Deposited: 02 Jul 2013 08:31
Last Modified: 23 Oct 2018 14:50
URI: http://eprints.iisc.ac.in/id/eprint/46622

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