Reciprocal Recommenders

نویسندگان

  • Luiz Pizzato
  • Tomek Rej
  • Thomas Chung
  • Kalina Yacef
  • Irena Koprinska
  • Judy Kay
چکیده

This paper introduces Reciprocal Recommenders, an important class of personalised recommender systems that has received little attention until now. The applications of Reciprocal Recommenders include online systems that help users to nd a job, a mentor, a business partner or even a date. The contributions of this paper are the de nition of this class of recommendation system, the identi cation of the particular personalisation challenges for them, the proposition of some promising techniques to address these challenges. We illustrate these concepts with a case study in online dating.

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تاریخ انتشار 2010