Algorithm Research & Explore
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1390-1395

Method based on word meaning and word frequency to improve vector space model

Deng Xiaoheng
Yang Zirong
Guan Peiyuan
School of Software, Central South University, Changsha 410075, China

Abstract

When the text content is more, the traditional VSM model may produce the dimension explosion phenomenon, the efficiency is low and the classification effect is difficult to guarantee. Aiming at the phenomenon of VSM, this paper proposed a method to reduce the dimension of text modeling by means of word meaning and frequency, in order to improve efficiency and accuracy. This paper proposed a synonym clustering method for polysemy discriminant optimization, combining with the context distinguishing word meaning, weighted by the similarity of the word meaning, and merging the feature items with similar meanings. The new method greatly reduced the dimension of eigenvector, and polysemy improved the accuracy of feature extraction. Compared with other text feature extraction and text categorization methods, the results show that the algorithm has a significant improvement in efficiency and accuracy.

Foundation Support

中南大学研究生创新基金资助项目(2017zzts732)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.12.0752
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 5
Section: Algorithm Research & Explore
Pages: 1390-1395
Serial Number: 1001-3695(2019)05-023-1390-06

Publish History

[2019-05-05] Printed Article

Cite This Article

邓晓衡, 杨子荣, 关培源. 一种基于词义和词频的向量空间模型改进方法 [J]. 计算机应用研究, 2019, 36 (5): 1390-1395. (Deng Xiaoheng, Yang Zirong, Guan Peiyuan. Method based on word meaning and word frequency to improve vector space model [J]. Application Research of Computers, 2019, 36 (5): 1390-1395. )

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  • Application Research of Computers Monthly Journal
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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.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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