Computer Science ›› 2017, Vol. 44 ›› Issue (Z11): 92-97.doi: 10.11896/j.issn.1002-137X.2017.11A.018

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Research of Text Sentiment Classification Based on Improved Semantic Comprehension

WANG Ri-hong, CUI Xing-mei, ZHOU Wei, WANG Cheng-long and LI Yong-jun   

  • Online:2018-12-01 Published:2018-12-01

Abstract: Text classification has a wide range of applications in information retrieval,Web automatic document classification,digital library,automatic abstracting,document organization and management.An improved text sentiment classification method was put forward based on semantic understanding.Emotional sememe was joined to revise the definition in the emotional similarity calculation and the development of emotional phrases’ sentiment was combined.Focusing on emotional words and negative words,the degree of adverbs combining form of analysis,and module complex negative word and adverb were put forward.Combining with the use of conjunctions as the standard of the sentence for emotional tendencies classified processing,a text propensity algorithm was given to judge the text sentiment and classify the text.Experimental results show that the classification results with the method improve when comparing with the previous algorithm.

Key words: Improved semantic comprehension,Text sentiment classification,Negative words,Adverb of degree,Sentence structure template

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