A decision tree using ID3 algorithm for English semantic analysis

被引：30
作者：
Phu V.N. [1 ]
Tran V.T.N. [2 ]
Chau V.T.N. [3 ]
Dat N.D. [4 ]
Duy K.L.D. [5 ]
机构：
[1] Institute of Research and Development, Duy Tan University - DTU, Da Nang
[2] School of Industrial Management (SIM), Ho Chi Minh City University of Technology - HCMUT, Vietnam National University, Ho Chi Minh City
[3] Computer Science & Engineering (CSE), Ho Chi Minh City University of Technology - HCMUT, Vietnam National University, Ho Chi Minh City
[4] Faculty of Information Technology, Ly Tu Trong Technical College, Ho Chi Minh City
[5] Faculty of Information Technology, Ho Chi Minh City University of Foreign Languages, Ho Chi Minh City
来源：
International Journal of Speech Technology | 2017年 / 20卷 / 03期
关键词：
Decision tree; English document opinion mining; English sentiment classification; ID3; algorithm; id3; Sentiment classification;
D O I：
10.1007/s10772-017-9429-x
中图分类号：
学科分类号：
摘要：
Natural language processing has been studied for many years, and it has been applied to many researches and commercial applications. A new model is proposed in this paper, and is used in the English document-level emotional classification. In this survey, we proposed a new model by using an ID3 algorithm of a decision tree to classify semantics (positive, negative, and neutral) for the English documents. The semantic classification of our model is based on many rules which are generated by applying the ID3 algorithm to 115,000 English sentences of our English training data set. We test our new model on the English testing data set including 25,000 English documents, and achieve 63.6% accuracy of sentiment classification results. © 2017, Springer Science+Business Media, LLC.
引用
收藏
页码：593 / 613
页数：20
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