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Getting to know you: Learning new user preferences in recommender systems

by: A. Rashid, I. Albert, D. Cosley, S. Lam, S. Mcnee, J. Konstan, and J. Riedl

(2002) .

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URL:	http://citeseer.ist.psu.edu/rashid02getting.html

Recommender systems have become valuable resources for users seeking intelligent ways to search through the enormous volume of information available to them. One crucial unsolved problem for recommender systems is how best to learn about a new user. In this paper we study six techniques that collaborative filtering recommender systems can use to learn about new users. These techniques select a sequence of items for the collaborative filtering system to present to each new user for rating. The...

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library2.0

BibTeX record

@misc{citeulike:463052,
  abstract = {Recommender systems have become valuable resources for
users seeking intelligent ways to search through the
enormous volume of information available to them. One
crucial unsolved problem for recommender systems is how
best to learn about a new user. In this paper we study six
techniques that collaborative filtering recommender
systems can use to learn about new users. These techniques
select a sequence of items for the collaborative filtering
system to present to each new user for rating. The...},
  added-at = {2007-04-17T15:32:58.000+0200},
  author = {Rashid, A. and Albert, I. and Cosley, D. and Lam, S. and Mcnee, S. and Konstan, J. and Riedl, J.},
  biburl = {http://www.bibsonomy.org/bibtex/247f50cd580fb3ce14665e12324f8cedd/patrickd},
  citeulike-article-id = {463052},
  description = {library2.0},
  interhash = {d1dae1ff3a30b3e8ef80a01e166e0e2c},
  intrahash = {47f50cd580fb3ce14665e12324f8cedd},
  keywords = {facebook for:Bibliothek2.0 library20 preference socialnetworking specific-search},
  timestamp = {2007-04-17T15:32:58.000+0200},
  title = {Getting to know you: Learning new user preferences in recommender systems},
  url = {http://citeseer.ist.psu.edu/rashid02getting.html},
  year = 2002
}

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