Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification

  title={Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification},
  author={Eui-Hong Han and George Karypis and Vipin Kumar},
Categorization of documents is challenging, as the number o f discriminating words can be very large. We present a nearest neighbor classification scheme for text categoriz ation in which the importance of discriminating words is learned using mutual information and weight adjustment tec hniques. The nearest neighbors for a particular document are then computed based on the matching words and their weigh ts. We evaluate our scheme on both synthetic and real world documents. Our experiments with… CONTINUE READING
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