A Collaborative Recommender System: Lexicographic Consensus and Web Usage Mining Approach

نویسندگان

  • Seok Kee Lee
  • Young-Gab Kim
  • Do-Gil Lee
چکیده

Collaborative filtering (CF) is one of the most successful and widely used methods of automated product recommendation domain [1, 2, 3]. However, cardinal scale generally used for representing the preference intensity is also ineffective owing to its increasing estimation errors. In this paper, we propose a new CF-based recommendation methodology that constructs an ordinal scale-based customer profile under the implicit ratings condition. An experiment with the Web transaction data from a real online shopping mall shows that the proposed method performs better than existing CF methodologies.

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تاریخ انتشار 2012