@inproceedings{mcnee2002recommending,
  abstract = {Collaborative filtering has proven to be valuable for recommending items in many different domains. In this paper, we explore the use of collaborative filtering to recommend research papers, using the citation web between papers to create the ratings matrix. Specifically, we tested the ability of collaborative filtering to recommend citations that would be suitable additional references for a target research paper. We investigated six algorithms for selecting citations, evaluating them through offline experiments against a database of over 186,000 research papers contained in ResearchIndex. We also performed an online experiment with over 120 users to gauge user opinion of the effectiveness of the algorithms and of the utility of such recommendations for common research tasks. We found large differences in the accuracy of the algorithms in the offline experiment, especially when balanced for coverage. In the online experiment, users felt they received quality recommendations, and were enthusiastic about the idea of receiving recommendations in this domain.},
  acmid = {587096},
  address = {New York, NY, USA},
  author = {McNee, Sean M. and Albert, Istvan and Cosley, Dan and Gopalkrishnan, Prateep and Lam, Shyong K. and Rashid, Al Mamunur and Konstan, Joseph A. and Riedl, John},
  booktitle = {Proceedings of the 2002 ACM conference on Computer supported cooperative work},
  doi = {10.1145/587078.587096},
  interhash = {7178849aab57a025dff76e177d64be9b},
  intrahash = {50f94e753fad76222bd33cbe591f9360},
  isbn = {1-58113-560-2},
  location = {New Orleans, Louisiana, USA},
  numpages = {10},
  pages = {116--125},
  publisher = {ACM},
  series = {CSCW '02},
  title = {On the recommending of citations for research papers},
  url = {http://doi.acm.org/10.1145/587078.587096},
  year = 2002
}

@inproceedings{sen2006tagging,
  abstract = {A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.},
  address = {New York, NY, USA},
  author = {Sen, Shilad and Lam, Shyong K. and Rashid, Al Mamunur and Cosley, Dan and Frankowski, Dan and Osterhouse, Jeremy and Harper, F. Maxwell and Riedl, John},
  booktitle = {CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work},
  doi = {10.1145/1180875.1180904},
  file = {sen2006tagging.pdf:sen2006tagging.pdf:PDF},
  groups = {public},
  interhash = {96b20bffcbc91e528461529935524b90},
  intrahash = {582641c05e7a0b9396945a951822c83f},
  isbn = {1-59593-249-6},
  location = {Banff, Alberta, Canada},
  pages = {181--190},
  publisher = {ACM},
  timestamp = {2011-02-02 15:10:48},
  title = {tagging, communities, vocabulary, evolution},
  url = {http://portal.acm.org/citation.cfm?id=1180904},
  username = {dbenz},
  year = 2006
}

@inproceedings{lam2004shilling,
  abstract = {Recommender systems have emerged in the past several years as an effective way to help people cope with the problem of information overload. One application in which they have become particularly common is in e-commerce, where recommendation of items can often help a customer find what she is interested in and, therefore can help drive sales. Unscrupulous producers in the never-ending quest for market penetration may find it profitable to shill recommender systems by lying to the systems in order to have their products recommended more often than those of their competitors. This paper explores four open questions that may affect the effectiveness of such shilling attacks: which recommender algorithm is being used, whether the application is producing recommendations or predictions, how detectable the attacks are by the operator of the system, and what the properties are of the items being attacked. The questions are explored experimentally on a large data set of movie ratings. Taken together, the results of the paper suggest that new ways must be used to evaluate and detect shilling attacks on recommender systems.},
  address = {New York, NY, USA},
  author = {Lam, Shyong K. and Riedl, John},
  booktitle = {WWW '04: Proceedings of the 13th International Conference on World Wide Web},
  doi = {10.1145/988672.988726},
  interhash = {66e00212d44132e4d2ff6968a10999d4},
  intrahash = {fa20593a49577529fdde250fc6d15110},
  isbn = {1-58113-844-X},
  location = {New York, NY, USA},
  pages = {393--402},
  publisher = {ACM},
  title = {Shilling recommender systems for fun and profit},
  url = {http://portal.acm.org/citation.cfm?id=988726&dl=GUIDE&coll=GUIDE&CFID=62005989&CFTOKEN=12250743},
  year = 2004
}

@inproceedings{cosley2003believing,
  abstract = {Recommender systems use people's opinions about items in an information domain to help people choose other items. These systems have succeeded in domains as diverse as movies, news articles, Web pages, and wines. The psychological literature on conformity suggests that in the course of helping people make choices, these systems probably affect users' opinions of the items. If opinions are influenced by recommendations, they might be less valuable for making recommendations for other users. Further, manipulators who seek to make the system generate artificially high or low recommendations might benefit if their efforts influence users to change the opinions they contribute to the recommender. We study two aspects of recommender system interfaces that may affect users' opinions: the rating scale and the display of predictions at the time users rate items. We find that users rate fairly consistently across rating scales. Users can be manipulated, though, tending to rate toward the prediction the system shows, whether the prediction is accurate or not. However, users can detect systems that manipulate predictions. We discuss how designers of recommender systems might react to these findings.},
  address = {New York, NY, USA},
  author = {Cosley, Dan and Lam, Shyong K. and Albert, Istvan and Konstan, Joseph A. and Riedl, John},
  booktitle = {CHI '03: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems},
  doi = {10.1145/642611.642713},
  interhash = {1b7ceacc5ada8aecc41e6684c0852702},
  intrahash = {30230be1037c17a6ff958eb66b45d3a3},
  isbn = {1-58113-630-7},
  location = {Ft. Lauderdale, Florida, USA},
  pages = {585--592},
  publisher = {ACM},
  title = {Is seeing believing?: how recommender system interfaces affect users' opinions},
  url = {http://portal.acm.org/citation.cfm?id=642611.642713&type=series},
  year = 2003
}

@inproceedings{citeulike:965334,
  address = {New York, NY, USA},
  author = {Sen, Shilad and Lam, Shyong K. and Rashid, Al M. and Cosley, Dan and Frankowski, Dan and Osterhouse, Jeremy and Harper, Maxwell F. and Riedl, John},
  booktitle = {CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work},
  citeulike-article-id = {965334},
  doi = {10.1145/1180875.1180904},
  interhash = {4f52a489eb6a696353d083b4d81b1fed},
  intrahash = {25f189ea6ed05c1df70cd58a053b9798},
  isbn = {1595932496},
  pages = {181--190},
  posted-at = {2009-04-01 05:03:08},
  priority = {4},
  publisher = {ACM Press},
  title = {tagging, communities, vocabulary, evolution},
  url = {http://dx.doi.org/10.1145/1180875.1180904},
  year = 2006
}

@inproceedings{sen2006tagging,
  abstract = {A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.},
  address = {New York, NY, USA},
  author = {Sen, Shilad and Lam, Shyong K. and Rashid, Al Mamunur and Cosley, Dan and Frankowski, Dan and Osterhouse, Jeremy and Harper, F. Maxwell and Riedl, John},
  booktitle = {CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work},
  doi = {http://doi.acm.org/10.1145/1180875.1180904},
  interhash = {96b20bffcbc91e528461529935524b90},
  intrahash = {582641c05e7a0b9396945a951822c83f},
  isbn = {1-59593-249-6},
  location = {Banff, Alberta, Canada},
  pages = {181--190},
  publisher = {ACM},
  title = {tagging, communities, vocabulary, evolution},
  url = {http://portal.acm.org/citation.cfm?id=1180904},
  year = 2006
}

@inproceedings{1180904,
  abstract = {A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.},
  address = {New York, NY, USA},
  author = {Sen, Shilad and Lam, Shyong K. and Rashid, Al Mamunur and Cosley, Dan and Frankowski, Dan and Osterhouse, Jeremy and Harper, F. Maxwell and Riedl, John},
  booktitle = {CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work},
  doi = {http://doi.acm.org/10.1145/1180875.1180904},
  interhash = {96b20bffcbc91e528461529935524b90},
  intrahash = {582641c05e7a0b9396945a951822c83f},
  isbn = {1-59593-249-6},
  location = {Banff, Alberta, Canada},
  pages = {181--190},
  publisher = {ACM},
  title = {tagging, communities, vocabulary, evolution},
  url = {http://portal.acm.org/citation.cfm?id=1180904},
  year = 2006
}

@inproceedings{1180904,
  abstract = {A tagging community's vocabulary of tags forms the basis for social navigation and shared expression.We present a user-centric model of vocabulary evolution in tagging communities based on community influence and personal tendency. We evaluate our model in an emergent tagging system by introducing tagging features into the MovieLens recommender system.We explore four tag selection algorithms for displaying tags applied by other community members. We analyze the algorithms 'effect on vocabulary evolution, tag utility, tag adoption, and user satisfaction.},
  address = {New York, NY, USA},
  author = {Sen, Shilad and Lam, Shyong K. and Rashid, Al Mamunur and Cosley, Dan and Frankowski, Dan and Osterhouse, Jeremy and Harper, F. Maxwell and Riedl, John},
  booktitle = {CSCW '06: Proceedings of the 2006 20th anniversary conference on Computer supported cooperative work},
  doi = {http://doi.acm.org/10.1145/1180875.1180904},
  interhash = {96b20bffcbc91e528461529935524b90},
  intrahash = {582641c05e7a0b9396945a951822c83f},
  isbn = {1-59593-249-6},
  location = {Banff, Alberta, Canada},
  pages = {181--190},
  publisher = {ACM},
  title = {tagging, communities, vocabulary, evolution},
  url = {http://portal.acm.org/citation.cfm?id=1180904},
  year = 2006
}