Turning from TF-IDF to TF-IGM for term weighting in text classification

@article{Chen2016TurningFT,
  title={Turning from TF-IDF to TF-IGM for term weighting in text classification},
  author={Kewen Chen and Zuping Zhang and Jun Long and Hao Zhang},
  journal={Expert Syst. Appl.},
  year={2016},
  volume={66},
  pages={245-260}
}
Massive textual data management and mining usually rely on automatic text classification technology. Term weighting is a basic problem in text classification and directly affects the classification accuracy. Since the traditional TF-IDF (term frequency & inverse document frequency) is not fully effective for text classification, various alternatives have been proposed by researchers. In this paper we make comparative studies on different term weighting schemes and propose a new term weighting… CONTINUE READING

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