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GroupLens Research
A Grouplens Perspective
A Recommender System for Groups of Users
Community, Impact and Credit: Where Should I Submit My Papers?
Improvements in Holistic Recommender System Research
Truth and Lies of What People Are Really Thinking
User Session Identification Based on Strong Regularities in Inter-Activity
A Roll of the Dice
Evaluating Collaborative Filtering Recommender Systems
The Production and Consumption of Quality Content in Peer Production Communities
Item-Based Collaborative Filtering Recommendation Algorithms
Movielens Unplugged: Experiences with an Occasionally Connected Recommender System
Narayan Umn 0130M 20436.Pdf
C. Estelle Smith
C. Estelle Smith Curriculum Vitae
Technical Report
Tabletop Games in the Age of Remote Collaboration
Learning New User Preferences in Recommender Systems Al Mamunur Rashid, Istvan Albert, Dan Cosley, Shyong K
“Blissfully Happy” Or “Ready to Fight”: Varying Interpretations of Emoji
Top View
Rethinking the Recommender Research Ecosystem: Reproducibility, Openness, and Lenskit
Avoiding Pitfalls When Recommending Research Papers
Joseph A. Konstan |
The Identification of Deviance and Its Impact on Retention in a Multiplayer Game
The Next Stage of Recommender Systems Research Mark Van Setten Sean M
The LKPY Package for Recommender System Experiments
The Geography of Pokémon GO
Applied Data Mining This Page Intentionally Left Blank Applied Data Mining
Research Resources for Recommender Systems
Techniques for Improving Routing by Exploiting User Input and Behavior
Putting Users in Control of Their Recommendations
Bumpy, Caution with Merging: an Exploration of Tagging in a Geowiki
Towards a Better Understanding of Peer-Produced Structured Content Value
The Grouplens Research Project: About Me … Recommenders History of Recommender Systems the Early Years …
Being Accurate Is Not Enough: How Accuracy Metrics Have Hurt Recommender Systems
Time-Dependent Recommender Systems for the Prediction of Appropriate Learning Objects
Expanding Cyclopath Into a Statewide Bicycle Route-Finding Tool
Tagsplanations: Explaining Recommendations Using Tags