[Objective] This is an algorithm for improving the classification precision of Chinese text classification, which can calculate the similarity between Chinese texts more accurately. [Methods] With the TF-IDF algorithm calculating item weight and HowNet analyzing the semantic relationships between lexical items, this paper proposes a text similarity weighting algorithm based on HowNet semantics similarity, and makes an experiment on its Chinese text classification. [Results] The experiment resualts show that the proposed method can improve the text categorization performance comparing with the traditional ones. [Limitations] This algorithm is quite high in its time complexity, and its speed of text classification needs to be improved. [Conclusions] It is proved to be an effective algorithm for enhancing the classification accuracy of Chinese text by analyzing the semantic relationships between feature items.
刘怀亮, 杜坤, 秦春秀. 基于知网语义相似度的中文文本分类研究[J]. 现代图书情报技术, 2015, 31(2): 39-45.
Liu Huailiang, Du Kun, Qin Chunxiu. Research on Chinese Text Categorization Based on Semantic Similarity of HowNet. New Technology of Library and Information Service, 2015, 31(2): 39-45.
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