Relevance Feature Discovery for Text Mining

@article{Li2015RelevanceFD,
  title={Relevance Feature Discovery for Text Mining},
  author={Yuefeng Li and Abdulmohsen Algarni and Mubarak Albathan and Yan Shen and Moch Arif Bijaksana},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  year={2015},
  volume={27},
  pages={1656-1669}
}
It is a big challenge to guarantee the quality of discovered relevance features in text documents for describing user preferences because of large scale terms and data patterns. Most existing popular text mining and classification methods have adopted term-based approaches. However, they have all suffered from the problems of polysemy and synonymy. Over the years, there has been often held the hypothesis that pattern-based methods should perform better than term-based ones in describing user… CONTINUE READING
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