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XAI 기법을 이용한 리뷰 유용성 예측 결과 설명에 관한 연구
Explainable Artificial Intelligence Applied in Deep Learning for Review Helpfulness Prediction 원문보기

지능정보연구 = Journal of intelligence and information systems, v.29 no.2, 2023년, pp.35 - 56  

류동엽 (경희대학교 빅데이터 응용학과) ,  이흠철 (경희대학교 빅데이터 응용학과) ,  김재경 (경희대학교 경영대학 & 빅데이터 응용학과)

초록
AI-Helper 아이콘AI-Helper

정보통신 기술의 발전에 따라 웹 사이트에는 수많은 리뷰가 지속적으로 게시되고 있다. 이로 인해 정보 과부하 문제가 발생하여 사용자들은 본인이 원하는 리뷰를 탐색하는데 어려움을 겪고 있다. 따라서, 이러한 문제를 해결하여 사용자에게 유용하고 신뢰성 있는 리뷰를 제공하기 위해 리뷰 유용성 예측에 관한 연구가 활발히 진행되고 있다. 기존 연구는 주로 리뷰에 포함된 특성을 기반으로 리뷰 유용성을 예측하였다. 그러나, 예측한 리뷰가 왜 유용한지 근거를 제시할 수 없다는 한계점이 존재한다. 따라서 본 연구는 이러한 한계점을 해결하기 위해 리뷰 유용성 예측 모델에 eXplainable Artificial Intelligence(XAI) 기법을 적용하는 방법론을 제안하였다. 본 연구는 Yelp.com에서 수집한 레스토랑 리뷰를 사용하여 리뷰 유용성 예측에 관한 연구에서 널리 사용되는 6개의 모델을 통해 예측 성능을 비교하였다. 그 다음, 예측 성능이 가장 우수한 모델에 XAI 기법을 적용하여 설명 가능한 리뷰 유용성 예측 모델을 제안하였다. 따라서 본 연구에서 제안한 방법론은 사용자의 구매 의사결정 과정에서 유용한 리뷰를 추천할 수 있는 동시에 해당 리뷰가 왜 유용한지에 대한 해석을 제공할 수 있다.

Abstract ▼ AI-Helper 아이콘AI-Helper

With the development of information and communication technology, numerous reviews are continuously posted on websites, which causes information overload problems. Therefore, users face difficulty in exploring reviews for their decision-making. To solve such a problem, many studies on review helpful...

주제어

#리뷰 유용성   #머신러닝   #온라인 구전   #온라인 리뷰  

표/그림 (8)

참고문헌 (76)

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