Application of ant colony optimization for feature selection in text categorization

@article{Aghdam2008ApplicationOA,
  title={Application of ant colony optimization for feature selection in text categorization},
  author={Mehdi Hosseinzadeh Aghdam and N. Ghasem-Aghaee and Mohammad Ehsan Basiri},
  journal={2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)},
  year={2008},
  pages={2867-2873}
}
  • Mehdi Hosseinzadeh Aghdam, N. Ghasem-Aghaee, Mohammad Ehsan Basiri
  • Published 2008
  • Computer Science
  • 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence)
  • Feature selection is commonly used to reduce dimensionality of datasets with tens or hundreds of thousands of features. A major problem of text categorization is the high dimensionality of the feature space; therefore, feature selection is the most important step in text categorization. This paper presents a novel feature selection algorithm that is based on ant colony optimization. Ant colony optimization algorithm is inspired by observation on real ants in their search for the shortest paths… CONTINUE READING
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