Text Categorization using Feature Projections

This paper proposes a new approach for text categorization, based on a feature projection technique. In our approach, training data are represented as the projections of training documents on each feature. The voting for a classification is processed on the basis of individual feature projections. The final classification of test documents is determined by a majority voting from the individual classifications of each feature. Our empirical results show that the proposed approach, Text Categorization using Feature Projections (TCFP), outperforms k-NN, Rocchio, and Na

• Type: Journal
• Year: 2002
• Where: COLING
• Authors: Youngjoong Ko, Jungyun Seo
• Keywords: COLING 2002, COLING 2008, Feature Projection Technique, Feature Projections, Text Categorization