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Performance Improvement of Product Recommendation Methodology Using Social Network Analysis

  • Journal of Knowledge Information Technology and Systems
  • Abbr : JKITS
  • 2011, 6(2), pp.135-144
  • Publisher : Korea Knowledge Information Technology Society
  • Research Area : Interdisciplinary Studies > Interdisciplinary Research
  • Published : April 30, 2011

강부식 1

1목원대학교

Candidate

ABSTRACT

In the E-commerce environment, performance improvement is one of the main issues in the field of product recommendation systems. Collaborative filtering is a successful and popular method for recommender systems. It has some fundamental problems for new customer or new product recommendation. Recently, some studies using social network analysis has been presented to solve the problems. There are various analysis methods in the field of the social networks. Degree centrality and structural holes of them has been used mainly for recommender systems. This study suggested a methodology for performance improvement of the collaborative filtering process using degree centrality and structural holes methods. In experimental results for MovieLens datasets, this study showed the proposed methodology using structural holes can improve the performance of the recommendation system.

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