Significant Feature Clustering
In this thesis, we present a new clustering algorithm we call <em>Significance Feature Clustering</em>, which is designed to cluster text documents. Its central premise is the mapping of raw frequency count vectors to discrete-valued significance vectors which contain values of -1,...
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| Format: | Others |
| Language: | en |
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University of Waterloo
2007
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| Online Access: | http://hdl.handle.net/10012/2926 |