Journal of Korean Institute of Industrial Engineers (대한산업공학회지)

Korean Institute of Industrial Engineers (대한산업공학회)
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Development of a Recommender System for E-Commerce Sites Using a Dimensionality Reduction Technique

차원 감소 기법을 이용한 전자 상거래 추천 시스템

  • Kim, Yong-Soo (Department of Industrial and Management Engineering, Kyonggi University) ;
  • Yum, Bong-Jin (Department of Industrial and System Engineering, KAIST) ;
  • Kim, Nor-Man (RUTCOR, Rutgers, The State University of New Jersey)
  • 김용수 (경기대학교 산업경영공학과) ;
  • 염봉진 (KAIST 산업 및 시스템공학과) ;
  • Received : 2010.06.16
  • Accepted : 2010.08.20
  • Published : 2010.09.01
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Abstract

The recommender system is a typical software solution for personalized services which are now popular in e-commerce sites. Most of the existing recommender systems are based on customers' explicit rating data on items (e.g., ratings on movies), and it is only recently that recommender systems based on implicit ratings have been proposed as a better alternative. Implicit ratings of a customer on those items that are clicked but not purchased can be inferred from the customer's navigational and behavioral patterns. In this article, a dimensionality reduction (DR) technique is newly applied to the implicit rating-based recommender system, and its effectiveness is assessed using an experimental e-commerce site. The experimental results indicate that the performance of the proposed approach is superior or at least similar to the conventional collaborative filtering (CF)-based approach unless the number of recommended products is 'large.' In addition, the proposed approach requires less memory space and is computationally more efficient.

Keywords

References

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