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Expansion of Opinion Mining based on Entity Association Network Model

개체연관망 모델에 의한 오피니언마이닝의 확장

  • 김근형 (제주대학교 경영정보학과)
  • Received : 2011.01.24
  • Accepted : 2011.06.23
  • Published : 2011.08.31

Abstract

Opinion Mining summarizes with classifying sensitive opinions of customers in huge online customer reviews for the attributes of products or services by positive and negative opinions. Because the customers represent their interests through subjective opinions as well as objective facts, the existing opinion mining techniques, which can analyze just the sensitive opinions, need to be expanded.. In this paper, We propose the novel entity association network model which expands the existing opinion mining techniques. The entity association model can not only represent positive and negative degree of the sensitive opinions, but also can represent the degree of the associations and relative importances between entities. We designed and implemented the customer reviews analysis system based on the entity association network model. We recognized that the system can represent more abundant information than the existing opinion mining techniques.

오피니언마이닝은 대량의 온라인 고객리뷰에서 상품이나 서비스의 속성들에 대한 고객들의 주관적 의견을 긍정과 부정으로 분류하여 요약한다. 그러나, 고객들의 관심사항은 주관적 의견뿐만 아니라 객관적 사실을 통해서도 표현되기 때문에 주관적 의견만을 주요 분석대상으로 하는 기존 오피니언마이닝 기법을 확장할 필요가 있다. 본 논문에서는 주관적 의견뿐만 아니라 객관적 사실도 분석대상으로 하는 개체연관망 모델을 사용하여 기존 오피니언마이닝의 분석능력을 확장한다. 개체연관망 모델은 각 개체에 대한 긍정부정 정도를 표현할 뿐만 아니라 개체들 사이의 연관관계와 상대적 중요성을 나타낼 수 있다. 시스템 구현 결과, 개체연관망 모델에 기반한 오피니언마이닝시스템은 기존 기법에 비하여 보다 풍부한 정보를 추출할 수 있음을 확인하였다.

Keywords

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