Distributional Features for Text Categorization

  • Xiao-Bing Xue
  • Zhi-Hua Zhou
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4212)


In previous research of text categorization, a word is usually described by features which express that whether the word appears in the document or how frequently the word appears. Although these features are useful, they have not fully expressed the information contained in the document. In this paper, the distributional features are used to describe a word, which express the distribution of a word in a document. In detail, the compactness of the appearances of the word and the position of the first appearance of the word are characterized as features. These features are exploited by a TFIDF style equation in this paper. Experiments show that the distributional features are useful for text categorization. In contrast to using the traditional term frequency features solely, including the distributional features requires only a little additional cost, while the categorization performance can be significantly improved.


Distributional Feature Text Categorization Term Frequency Word Sense Disambiguation Usenet Newsgroup 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Xiao-Bing Xue
    • 1
  • Zhi-Hua Zhou
    • 1
  1. 1.National Laboratory for Novel Software TechnologyNanjing UniversityNanjingChina

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