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}
}
A new supervised term weighting scheme called TF-IGM is proposed.It adopts a new statistical model to measure a term's class distinguishing power.It makes full use of the fine-grained term distribution across different classes.It is adaptive to different text datasets by providing options or parameters.It outperforms TF-IDF and state-of-the-art supervised term weighting schemes. Massive textual data management and mining usually rely on automatic text classification technology. Term weighting… CONTINUE READING

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