Management Science and Financial Engineering

  • 제16권2호
  • /
  • Pages.53-65
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  • 2010
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  • 2287-2043(pISSN)
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  • 2287-2361(eISSN)
한국경영과학회 (The Korean Operations Research and Management Science Society)
권호 표지

Determining Absolute Interpolation Weights for Neighborhood-Based Collaborative Filtering

  • Kim, Hyoung-Do (School of Business Administration, Hanyang Cyber University)
  • 투고 : 2008.03.15
  • 심사 : 2009.12.20
  • 발행 : 2010.09.30
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초록

Despite the overall success of neighbor-based CF methods, there are some fundamental questions about neighbor selection and prediction mechanism including arbitrary similarity, over-fitting interpolation weights, no trust consideration between neighbours, etc. This paper proposes a simple method to compute absolute interpolation weights based on similarity values. In order to supplement the method, two schemes are additionally devised for high-quality neighbour selection and trust metrics based on co-ratings. The former requires that one or more neighbour's similarity should be better than a pre-specified level which is higher than the minimum level. The latter gives higher trust to neighbours that have more co-ratings. Experimental results show that the proposed method outperforms the pure IBCF by about 8% improvement. Furthermore, it can be easily combined with other predictors for achieving better prediction quality.

키워드

참고문헌

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