A new text feature conversion method for text classification

Authors:
Minghan Hu;Ying Liu;Lei Wang;Debin Ren
Affiliations:
College of Information Science & Engineering, Northeastern University, Shenyang, China;College of Information Science & Engineering, Northeastern University, Shenyang, China;College of Information Science & Engineering, Northeastern University, Shenyang, China;College of Information Science & Engineering, Northeastern University, Shenyang, China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
Year:
2009

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Abstract

Keywords normally carry large amount of category information. In order to fully utilize this kind of information for text classification, this paper proposes a new text feature conversion method based on the SKG model. The method uses the classified texts with the listed key words as the training data to train the classifier. To expand the keyword space, we construct the KWB model and do the text classification by combining the KWB model and the SKG model. The experiment results demonstrate the advantages of this new method.