Analysis on Content Multi-Classification of Chinese Tweets

被引：0

作者：

Li, Taowei ^{[1
]}

Jiang, Weiwei ^{[1
]}

Guo, Liang ^{[1
]}

Deng, Jingsheng ^{[1
]}

机构：

[1] Natl Univ Def Technol, Coll Informat Syst & Management, Changsha 410073, Hunan, Peoples R China

来源：

2ND INTERNATIONAL CONFERENCE ON SIMULATION AND MODELING METHODOLOGIES, TECHNOLOGIES AND APPLICATIONS (SMTA 2015) | 2015年

关键词：

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper focuses on messages classification in Chinese tweets without additional information. It classifies tweets into five valid categories-A, B, C, D, E and one invalid category-Other. The data only in five valid categories are trained, and the other category applies rejection method if the five valid categories deny it. To improve the efficiency of classification, we pre-process the data on three proposed rules. The precision of the improved-SVM (ISVM) algorithm we proposed is approximately 10% higher than Naive Bayesian classification and 1.3% higher than classical SVM.

引用

页码：51 / 54

页数：4

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