bias collaborative filtering collaborative systems contact recommendation context diversity evaluation finance group recommendation hybrid recommendation information extraction information retrieval information retrieval models information retrieval theory knn learning to rank link prediction metasearch metrics multi-armed bandits multimedia retrieval network monitoring news retrieval nlp non-random missing data novelty performance prediction personalization popularity probabilistic models rank aggregation rank fusion recommender systems relation extraction semantic search semantics social networks thompson sampling web search web services
J. Sanz-Cruzado, P. Castells, E. López.
A Simple Multi-Armed Nearest-Neighbor Bandit for Interactive Recommendation.
13th ACM Conference on Recommender Systems (RecSys 2019). Copenhagen, Denmark, September 2019, pp. 358-362.
R. Cañamares, P. Castells.
A Probabilistic Reformulation of Memory-Based Collaborative Filtering – Implications on Popularity Biases.
40th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2017). Tokyo, Japan, August 2017, pp. 215-224.