@inproceedings{wei03a,
  author =	 {Yan Zheng Wei and Luc Moreau and Nicholas
                  R. Jennings},
  title =	 {Recommender systems: a market-based design},
  booktitle =	 {Proceedings of the second international joint
                  conference on Autonomous agents and multiagent
                  systems},
  year =	 2003,
  pages =	 {600--607},
  location =	 {Melbourne, Australia},
  doi =		 {10.1145/860575.860671},
  publisher =	 {ACM Press, New York, NY.},
  abstract =	 {Recommender systems have been widely advocated as a
                  way of coping with the problem of information
                  overload for knowledge workers. Given this, multiple
                  recommendation methods have been developed. However,
                  it has been shown that no one technique is best for
                  all users in all situations. Thus we believe that
                  effective recommender systems should incorporate a
                  wide variety of such techniques and that some form
                  of overarching framework should be put in place to
                  coordinate the various recommendations so that only
                  the best of them (from whatever source) are
                  presented to the user. To this end, we show that a
                  marketplace, in which the various recommendation
                  methods compete to o er their recommendations to the
                  user, can be used in this role. Speci cally, this
                  paper presents the principled design of such a
                  marketplace; detailing the auction protocol and
                  reward mechanism and analyzing the rational bidding
                  strategies of the individual recommendation
                  agents.},
  keywords =     {recommender economics},
  url =		 {http://jmvidal.cse.sc.edu/library/wei03a.pdf},
  googleid = 	 {IkCIcPN2q34J:scholar.google.com/},
  comment =	 {masrg},
  cluster = 	 {9127519857733550114},
}