Tibetan Text Classification Based on the Feature of Position Weight

Abstract

Based on the study of Tibetan characters and grammar, this paper has done research on Tibetan in the text categorization weight algorithm based on the vector space model. Comprehensively considering the position information of Tibetan which presented in the text, the paper has proposed an improved TF-IDF weighting algorithm. In the process, it has adopted χ2 (CHI) statistical methods for features on the Tibetan word document extraction and used the cosine method in Tibetan text similarity calculation to distinguish between similar documents in Tibetan. The Tibetan text classification algorithm with linear separable support vector machine classification of Tibetan texts, and finally compared the TF-IDF algorithm with the improved TF-IDF algorithm in the effects of the Tibetan text classification. Finally, it shows that the improved TF-IDF algorithm has better classification effect.