A text classification method with an effective feature extraction based on category analysis
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 1
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International Journal of Information Retrieval Research
A pattern based two-stage text classifier
MLDM'13 Proceedings of the 9th international conference on Machine Learning and Data Mining in Pattern Recognition
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We present a novel feature selection (FS) approach for text categorization. It first constructs a local feature set for each category by selecting a set of features based on three different schemes: DF, TF and TFIDF, and then constructs a global feature set utilizing well-known CHI method based on the local feature set. The experimental comparison is carried out between our method and CHI method. Results from the experiments are summarized. The results show that our proposed method based on DF scheme can perform comparatively well with CHI methods.