Abstract
This paper explores the possibilities of using independent component analysis (ICA) for features extraction that could be applied to word sense induction. Two different methods for using the features derived by ICA are introduced and results evaluated. Our goal in this paper is to observe whether ICA based feature vectors can be efficiently used for word context encoding and subsequently for clustering. We show that it is possible, further research is, however, necessary to ascertain more reliable results.
| Original language | English |
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| Publication status | Published - 2007 |
| Externally published | Yes |
| Event | 19th Conference on Computational Linguistics and Speech Processing, ROCLING 2007 - Taipei, Taiwan Duration: 2007 Sept 6 → 2007 Sept 7 |
Other
| Other | 19th Conference on Computational Linguistics and Speech Processing, ROCLING 2007 |
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| Country/Territory | Taiwan |
| City | Taipei |
| Period | 2007/09/06 → 2007/09/07 |
ASJC Scopus subject areas
- Language and Linguistics
- Speech and Hearing