Grading System of Movie Review through the Use of An Appraisal Dictionary and Computation of Semantic Segments

감정어휘 평가사전과 의미마디 연산을 이용한 영화평 등급화 시스템

  • Received : 2010.10.19
  • Accepted : 2010.12.02
  • Published : 2010.12.31


Assuming that the whole meaning of a document is a composition of the meanings of each part, this paper proposes to study the automatic grading of movie reviews which contain sentimental expressions. This will be accomplished by calculating the values of semantic segments and performing data classification for each review. The ARSSA(The Automatic Rating System for Sentiment analysis using an Appraisal dictionary) system is an effort to model decision making processes in a manner similar to that of the human mind. This aims to resolve the discontinuity between the numerical ranking and textual rationalization present in the binary structure of the current review rating system: {rate: review}. This model can be realized by performing analysis on the abstract menas extracted from each review. The performance of this system was experimentally calculated by performing a 10-fold Cross-Validation test of 1000 reviews obtained from the Naver Movie site. The system achieved an 85% F1 Score when compared to predefined values using a predefined appraisal dictionary.


Appraisal Dictionary;Synonymy;Synset;Grading;Semantic segment;SVM;ARSSA


Supported by : 한국학술진흥재단