Enhancing the Performance of Recommender Systems Using Online Review Clusters 


Vol. 45,  No. 2, pp. 126-133, Feb.  2018
10.5626/JOK.2018.45.2.126


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  Abstract

The recommender system (RS) has emerged as a solution to overcome the constraints of excessive information provision and to maximize profit and reputation for information providers. Although the RS can be implemented with various approaches, there is no study on how to appropriately utilize the information generated from the review of the recommended object. We propose a method to improve the performance of RS by using cluster information generated from online review. We implemented the proposed method and experimented with real data, and confirmed that the performance is significantly improved compared to the existing approaches.


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  Cite this article

[IEEE Style]

G. Noh, H. Oh, J. Lee, "Enhancing the Performance of Recommender Systems Using Online Review Clusters," Journal of KIISE, JOK, vol. 45, no. 2, pp. 126-133, 2018. DOI: 10.5626/JOK.2018.45.2.126.


[ACM Style]

Giseop Noh, Hayoung Oh, and Jaehoon Lee. 2018. Enhancing the Performance of Recommender Systems Using Online Review Clusters. Journal of KIISE, JOK, 45, 2, (2018), 126-133. DOI: 10.5626/JOK.2018.45.2.126.


[KCI Style]

노기섭, 오하영, 이재훈, "온라인 리뷰 클러스터를 이용한 추천 시스템 성능 향상," 한국정보과학회 논문지, 제45권, 제2호, 126~133쪽, 2018. DOI: 10.5626/JOK.2018.45.2.126.


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