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Modified Collaborative Filtering Algorithm Based on ItemRank

Author

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  • Pengyuan Xu

    (Institute of System Engineering, Dalian University of Technology, Dalian, China)

  • Yanzhong Dang

    (Institute of System Engineering, Dalian University of Technology, Dalian, China)

Abstract

The most crucial component of collaborative filtering recommendation algorithm (CF) is the mechanism of calculating similarities among items or users. In this paper, a new CF algorithm based on ItemRank Similarity (IRS) is proposed, which extracts items' quality characteristics from the similar matrix. The corresponding algorithmic accuracy is measured by the ranking score, precision, recall and F-measure. This algorithm provides remarkably higher accurate predictions than other modified CF algorithm.

Suggested Citation

  • Pengyuan Xu & Yanzhong Dang, 2014. "Modified Collaborative Filtering Algorithm Based on ItemRank," International Journal of Knowledge and Systems Science (IJKSS), IGI Global, vol. 5(1), pages 27-35, January.
    • Handle: RePEc:igg:jkss00:v:5:y:2014:i:1:p:27-35
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