Experimental Study for Effective Combination of Opinion Features

의견 검색은 사용자의 정보 요구에 주제적으로 연관되면서도 의견이 포함되어 있는 정보를 검색하는 태스크이다. 본 연구는 효과적인 의견 검색을 위해 사용자 정보 요구를 표현하는 방법과 이 요구를 만족시킬만한 여러 의견 자질들을 효과적으로 결합할 수 있는 방법에 대하여 실험을 통해 분석하였다. 본 실험에서는 추론 네트워크 모델을 기본 검색 모델로 사용하였고, Blogs06 컬렉션과 100개의 TREC 토픽에 대해 실험을 수행하였다. 실험 결과, 가상의 ‘의견’ 개념을 설정하여 효과적으로 의견 검색의 정보 요구를 표현할 수 있었으며, 극히 소량의 일반 의견 단어집만을 사용했는데도 동일한 환경에서 기존 모델과 견줄 만한 의견 검색 성능을 달성할 수 있었다.

keywords: 의견 검색, 의견 마이닝, 자질 결합, 질의 확장, 의견 단어집, opinion retrieval, opinion mining, feature combination, query expansion, opinion lexicon, opinion retrieval, opinion mining, feature combination, query expansion, opinion lexicon

Abstract

Opinion retrieval is to retrieve items which are relevant to the user information need topically and include opinion about the topic. This paper aims to find a method to represent user information need for effective opinion retrieval and to analyze the combination methods for opinion features through various experiments. The experiments are carried out in the inference network framework using the Blogs06 collection and 100 TREC test topics. The results show that our suggested representation method based on hidden ‘opinion’ concept is effective, and the compact model with very small opinion lexicon shows the comparable performance to the previous model on the same test data set.

keywords: 의견 검색, 의견 마이닝, 자질 결합, 질의 확장, 의견 단어집, opinion retrieval, opinion mining, feature combination, query expansion, opinion lexicon, opinion retrieval, opinion mining, feature combination, query expansion, opinion lexicon

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논문 상세

Vol.27 No.3

효과적인 의견 자질 결합을 위한 실험적 연구

Experimental Study for Effective Combination of Opinion Features

초록

Abstract

참고문헌

정보관리학회지