An effective category classification method based on a language model for question category recommendation on a cQA service

Classiying user's question into several topics helps respondents answering the question in a cQA service. The word weighting method must estimate the appropriate weight of a word to improve the category (or topic) classification. In this paper, we propose a novel effective word weighting method based on a language model for automatic category classification in the cQA service. We first calculate the occurrence probability of a word in each category by using a language model and then the final weight of each word is estimated by ratio of the occurrence probability of the word on a category to the occurrence probability of the word on the other categories. As a result, the proposed method significantly improves the performance of the category classification.