Algorithm Research & Explore
|
337-341

Text sentiment analysis based on hybrid mutual information algorithm

Wang Yi
Dai Yueming
School of Internet of Things Engineering, Jiangnan University, Wuxi Jiangsu 214122, China

Abstract

Aiming at the phenomenon of positive and negative correlation in the feature selection method of mutual information(MI) and the problem of the word frequency of the feature items in different categories hadn't been considered, this paper proposed a hybrid mutual information(HMI) feature selection algorithm. By introducing the inverse document frequency coefficient and the inter-class word frequency information coefficient, the algorithm could effectively utilize the word frequency information in the whole document and the word frequency information between each class. It introduced the positive and negative correlation coefficient to distinguish positive correlation and negative correlation and made effective use. The experimental results show that the hybrid mutual information algorithm can effectively improve the quality of feature selection and then improve the effect of text emotional analysis.

Foundation Support

国家自然科学基金资助项目(61572237)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.08.0537
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 2
Section: Algorithm Research & Explore
Pages: 337-341
Serial Number: 1001-3695(2020)02-004-0337-05

Publish History

[2020-02-05] Printed Article

Cite This Article

王义, 戴月明. 基于混合互信息算法的文本情感分析 [J]. 计算机应用研究, 2020, 37 (2): 337-341. (Wang Yi, Dai Yueming. Text sentiment analysis based on hybrid mutual information algorithm [J]. Application Research of Computers, 2020, 37 (2): 337-341. )

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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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