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Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008)
An Extensive Empirical Study of Feature Selection for Text Categorization
May 14-May 16
ISBN: 978-0-7695-3131-1
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.
Index Terms:
feature selection, Text Categorization
Citation:
Li-Qing Qiu, Ru-Yi Zhao, Gang Zhou, Sheng-Wei Yi, "An Extensive Empirical Study of Feature Selection for Text Categorization," icis, pp.312-315, Seventh IEEE/ACIS International Conference on Computer and Information Science (icis 2008), 2008
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