Title :
A New Text Feature Conversion Method for Text Classification
Author :
Hu, Minghan ; Liu, Ying ; Wang, Lei ; Ren, Debin
Author_Institution :
Coll. of Inf. Sci. & Eng., Northeastern Univ. (NEU), Shenyang, China
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.
Keywords :
pattern classification; stochastic processes; text analysis; keywords bootstrapping model; stochastic keyword generation model; text classification; text feature conversion method; Educational institutions; Frequency shift keying; Fuzzy systems; Information science; Knowledge engineering; Mutual information; Space technology; Stochastic processes; Text categorization; Training data; Bootstrapping; SKG model; feature conversion; text classification;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3735-1
DOI :
10.1109/FSKD.2009.579
