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GroupLens Research
Results: 175

#	Item
81	Short and Tweet: Experiments on Recommending Content from Information Streams Jilin Chen, Rowan Nairn†, Les Nelson†, Michael Bernstein∆, Ed H. Chi† University of Minnesota Add to Reading List Source URL: www-users.cs.umn.edu Language: English - Date: 2010-01-20 19:51:16 Internet search engines Technology Recommender systems Real-time web Text messaging Twitter GroupLens Research Collaborative filtering Cold start World Wide Web Collective intelligence Information science
82	Opportunity Fund 2015 Application Form Application Date: Applicant Information Student`s Full Name: Add to Reading List Source URL: photos.state.gov Language: English - Date: 2015-03-18 09:54:41 Question Education Linguistics Science GroupLens Research Recommender system Yes and no TOEFL
83	User Model User-Adap Inter[removed]:101–123 DOI[removed]s11257[removed]x ORIGINAL PAPER Recommender systems: from algorithms to user experience Add to Reading List Source URL: blog.namics.com Language: English - Date: 2013-02-14 03:12:07 Recommender systems Information retrieval Information systems GroupLens Research Collaborative filtering Cold start Information filtering system MovieLens Personalization Information science Human–computer interaction Collective intelligence
84	Predicting Users’ Preference from Tag Relevance Tien T. Nguyen and John Riedl GroupLens Research, Computer Science and Engineering, University of Minnesota, Minneapolis, MN[removed]removed], [removed] http Add to Reading List Source URL: grouplens.org Language: English - Date: 2013-09-24 12:58:16 Information retrieval Collective intelligence Recommender system GroupLens Research Web 2.0 Support vector machine Tag Netflix Prize Information science Information Statistics
85	The Identification of Deviance and its Impact on Retention in a Multiplayer Game Kenneth Shores GroupLens Research University of Minnesota, Minneapolis, MN 55455 Add to Reading List Source URL: files.grouplens.org Language: English - Date: 2013-11-03 18:56:53 Human behavior Behavior Deviance Social philosophy Labeling theory Workplace deviance Norm Deviant Behavior Toxicity Sociology Criminology Sociological terms
86	Recommenders Everywhere: The WikiLens Community-Maintained Recommender System Dan Frankowski, Shyong K. (Tony) Lam, Shilad Sen, F. Maxwell Harper, Scott Yilek, Michael Cassano, John Riedl GroupLens Research, University o Add to Reading List Source URL: www-users.cs.umn.edu Language: English - Date: 2007-09-05 13:54:20 Human–computer interaction Information retrieval Science Collaboration Web 2.0 GroupLens Research Recommender system Collaborative filtering Information filtering system Information science Information Collective intelligence
87	Applying Collaborative Filtering Techniques to Movie Search for Better Ranking and Browsing Seung-Taek Park David M. Pennock Add to Reading List Source URL: dpennock.com Language: English - Date: 2007-11-08 11:48:21 Collective intelligence Information systems Collaboration Recommender system Collaborative filtering Yahoo! Bing GroupLens Research Cold start Information science Information retrieval Internet search engines
88	More Efficient Tagging Systems with Tag Seeding 1 Vikas Kumar1 , Daniel Kluver1 , Loren Terveen1 , John Riedl1 GroupLens Research - University of Minnesota, Twin Cities, USA vikas,kluver,[removed] Add to Reading List Source URL: www-users.cs.umn.edu Language: English - Date: 2014-07-23 18:52:33 Social information processing Collective intelligence Information retrieval Metadata Tag GroupLens Research Flickr Polyhistidine-tag Models of collaborative tagging Information Web 2.0 World Wide Web
89	Workshop on Social Recommender Systems Ido Guy Li Chen Michelle X. Zhou Add to Reading List Source URL: www.research.ibm.com Language: English - Date: 2011-02-01 07:35:33 Collective intelligence Collaboration Information systems Collaborative filtering Information filtering system GroupLens Research Easyrec Social information processing Information science Recommender systems
90	The Chasms of CSCW: A Citation Graph Analysis of the CSCW Conference Michal Jacovi, Vladimir Soroka, Gail Gilboa-Freedman, Sigalit Ur, Elad Shahar Natalia Marmasse* Add to Reading List Source URL: www.research.ibm.com Language: English - Date: 2011-02-01 07:35:36 Groupware Software Multimodal interaction Computing Computer-supported cooperative work Jonathan Grudin GroupLens Research Collaborative software Cluster analysis Humanâ€“computer interaction Human–computer interaction Collaboration