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.
Full text not available from this repository. (Request a copy)Abstract
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 |
|---|---|
| Publisher: | Springer Berlin Heidelberg |
| 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 |
| 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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