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GroupLens Research
Results: 175

#	Item
101	Web Mining Introduction to Mahout and Taste Universität Mannheim – Bizer/Meusel/Lehmberg/Zirn: Web Mining – FSS2014 (Version: [removed]) – Slide 1 Add to Reading List Source URL: dws.informatik.uni-mannheim.de Language: English - Date: 2014-09-29 11:42:15 Collective intelligence Social information processing Collaboration Collaborative filtering Information retrieval Recommender system GroupLens Research Apache Hadoop K-means clustering Information science Statistics Computing
102	An Analysis of Recommender Algorithms for Online News Doychin Doychev, Aonghus Lawlor, Rachael Rafter, and Barry Smyth Insight Centre for Data Analytics, University College Dublin Belfield, Dublin 4, Ireland. {firstname. Add to Reading List Source URL: ceur-ws.org Language: English - Date: 2014-07-25 04:51:02 Collective intelligence Information retrieval Collaborative filtering Science Information HTTP cookie GroupLens Research Recommender systems Information science Social information processing
103	Summary of the 15th Discovery Challenge Recommending Given Names Folke Mitzlaff1 , Stephan Doerfel1 , Andreas Hotho2,3 , Robert J¨aschke3 , and Juergen Mueller1,3 1 Add to Reading List Source URL: ceur-ws.org Language: English - Date: 2014-01-24 08:58:52 Information Collaboration Recommender system Collaborative filtering Twitter Bing HTTP cookie GroupLens Research Information science Information retrieval World Wide Web
104	WP:Clubhouse? An Exploration of Wikipedia’s Gender Imbalance Shyong (Tony) K. Lam1 , Anuradha Uduwage1 , Zhenhua Dong2 , Shilad Sen3 , David R. Musicant4 , Loren Terveen1 , John Riedl1 1 GroupLens Research Dept. of Com Add to Reading List Source URL: www-users.cs.umn.edu Language: English - Date: 2012-03-06 12:48:59 Science Gender Open content Biology Sociology Wikipedia GroupLens Research Transgender Sexism Human–computer interaction Gender studies Behavior
105	Microsoft Word - crowdrec_workshop_v7 Add to Reading List Source URL: crowdrec2013.noahlab.com.hk Language: English - Date: 2013-10-04 00:02:28 Social information processing Collaboration Recommender systems Cold start Information filtering system Crowdsourcing Human-based computation GroupLens Research Collaborative filtering Information systems Collective intelligence Information science
106	R Foundations and Trends in Human–Computer Interaction Vol. 4, No[removed]–173 c 2011 M. D. Ekstrand, J. T. Riedl and J. A. Konstan Add to Reading List Source URL: files.grouplens.org Language: English - Date: 2011-09-19 15:41:05 Recommender systems Collective intelligence Social information processing GroupLens Research Collaborative filtering Personalization Cold start Guided selling Information science Information retrieval Human–computer interaction
107	Enhancement of the Neutrality in Recommendation Toshihiro Kamishima, Shotaro Akaho, and Hideki Asoh National Institute of Advanced Industrial Science and Technology (AIST) AIST Tsukuba Central 2, Umezono 1-1-1, Add to Reading List Source URL: recex.ist.tugraz.at Language: English - Date: 2012-09-08 17:28:10 Information Science Recommender systems Social information processing Collective intelligence GroupLens Research Collaborative filtering Filter bubble Information filtering system Information science Human–computer interaction Information retrieval
108	Microsoft Word - RecSys_RUE2012_v6(CameraReady) Add to Reading List Source URL: ir.ii.uam.es Language: English - Date: 2012-09-25 10:47:46 Information retrieval Collaboration Collective intelligence Social information processing Recommender system Collaborative filtering GroupLens Research Netflix Prize Netflix Algebra Mathematics Statistics
109	Insights on Social Recommender System Wolney L. de Mello Neto Ann Nowé Vrije Universiteit Brussel Add to Reading List Source URL: ir.ii.uam.es Language: English - Date: 2012-09-28 09:54:58 Social information processing Information retrieval Human–computer interaction Information Recommender system Collaborative filtering Cold start GroupLens Research Personalization Information science Collaboration Collective intelligence
110	CLiMF: Learning to Maximize Reciprocal Rank with Collaborative Less-is-More Filtering ∗ Yue Shi Add to Reading List Source URL: www.ci.tuwien.ac.at Language: English - Date: 2012-07-25 17:33:29 Collaborative filtering Recommender system Learning to rank GroupLens Research Information filtering system Personalization Precision and recall Relevance Information science Information retrieval Science

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