Text Classification by Augmenting Bag of Words (BOW) Representation with Co-occurrence Feature

  • George K S
  • Joseph S
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Abstract

Text classification is the task of assigning predefined categories to free-text documents based on their content. Traditional approaches used unigram based models for text classification. Unigram based models such as Bag Of Words(BOW) models are not considering co-occurrence of set of words in a document level. This paper proposes a way to find co-occurrence feature from anchor text of wikipedia pages, proposes a way to incorporate co-occurrence feature to BOW model. Finally the method is analyzed to know how it performs in task of text classification.

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George K, S., & Joseph, S. (2014). Text Classification by Augmenting Bag of Words (BOW) Representation with Co-occurrence Feature. IOSR Journal of Computer Engineering, 16(1), 34–38. https://doi.org/10.9790/0661-16153438

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