Abstract

Giving further consideration on linguistic feature, this study proposes an algorithm of Chinese text categorization based on sense group. The algorithm extracts sense group by analyzing syntactic and semantic properties of Chinese texts and builds the category sense group library. SVM is used for the experiment of text categorization. The experimental results show that the precision and recall of the new algorithm based on sense group is better than that of traditional algorithms.

Keywords:

Semantic concept, sense group, support vector machine, text categorization,

References

Competing interests

The authors have no competing interests.

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Copyright

The authors have no competing interests.