Conference proceeding
Spectral document clustering algorithms with different data structures
CSC '05: PROCEEDINGS OF THE 2005 INTERNATIONAL CONFERENCE ON SCIENTIFIC COMPUTING, pp.223-229
01/01/2005
Abstract
Spectral document clustering methods construct sparse word-document matrix W to measure the difference or similarity of documents. It may produce a dense similarity matrix S with W-T X W. We presented a multilevel algorithm on S in [9]. The spectral clustering algorithms on S work well when the size of the dataset is not too big. However, the multiplication for S takes too much time even with efficient sparse multiplication. In this paper, we present a variant of the algorithm on W and investigate two algorithms with computational experiments.
Details
- Title: Subtitle
- Spectral document clustering algorithms with different data structures
- Creators
- S OliveiraS C Seok
- Contributors
- H R Arabnia (Editor)G A Gravvanis (Editor)
- Resource Type
- Conference proceeding
- Publication Details
- CSC '05: PROCEEDINGS OF THE 2005 INTERNATIONAL CONFERENCE ON SCIENTIFIC COMPUTING, pp.223-229
- Publisher
- C S R E A Press
- Number of pages
- 7
- Language
- English
- Date published
- 01/01/2005
- Academic Unit
- Mathematics; Computer Science
- Record Identifier
- 9984411084702771
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