A decision tree using ID3 algorithm for English semantic analysis

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 algo...

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Bibliographic Details
Published in:International journal of speech technology 2017-09, Vol.20 (3), p.593-613
Main Authors: Phu, Vo Ngoc, Tran, Vo Thi Ngoc, Chau, Vo Thi Ngoc, Dat, Nguyen Duy, Duy, Khanh Ly Doan
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Classification
Decision analysis
Decision trees
Engineering
English language
Natural language processing
Semantic analysis
Semantics
Sentences
Sentiment analysis
Signal,Image and Speech Processing
Social Sciences
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Summary: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.
ISSN:1381-2416
1572-8110
DOI:10.1007/s10772-017-9429-x