Posters
Discovering latent factors from movies genres for enhanced recommendation
by Marcelo Manzato
Constrained Collective Matrix Factorization
by Yujia Huang, Evan Xiang and Rong Pan
The influence of knowledgeable explanations on users’ perception of a recommender system
by Markus Zanker
Influential Seed Items Recommendation
by Qi Liu, Biao Xiang, Enhong Chen, Yong Ge, Hui Xiong and Tengfei Bao
Design and Evaluation of a Group Recommender System
by Toon De Pessemier, Simon Dooms and Luc Martens
Using Graph Partitioning Techniques for Neighbour Selection in User-Based Collaborative Filtering
by Alejandro Bellogin and Javier Parapar
Dynamic Personalized Recommendation of Comment-Eliciting Stories
by Michal Aharon, Amit Kagian, Ronny Lempel and Yehuda Koren
Collaborative Learning of Preference Rankings
by Tim Salimans, Thore Graepel and Ulrich Paquet
Recommending Academic Papers via Users’ Reading Purposes
by Yichen Jiang, Aixia Jia, Yansong Feng and Dongyan Zhao
Local Learning of Item Dissimilarity Using Content and Link Structure
by Abir De, Maunendra Sankar Desarkar, Niloy Ganguly and Pabitra Mitra
Exploiting the Web of Data in Model-based Recommender Systems
by Roberto Mirizzi, Tommaso Di Noia, Vito Claudio Ostuni and Davide Romito
Probabilistic News Recommender Systems with Feedback
by Shankar Prawesh and Balaji Padmanabhan
Remembering the stars? Effect of time on preference retrieval from memory
by Dirk Bollen, Mark Graus and Martijn Willemsen
Swarming to Rank for Recommender Systems
by Ernesto Diaz-Aviles, Mihai Georgescu and Wolfgang Nejdl
When Recommenders Fail: Identifying and Predicting Recommender Failure for Evidence-Based Algorithm Selection and Combination
by Michael Ekstrand and John Riedl
Making Recommendations in a Microblog to Improve the Impact of a Focal User
by Shanchan Wu, Leanna Gong, William Rand and Louiqa Raschid
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