bias collaborative filtering collaborative systems contact recommendation context diversity ensembles evaluation false positive false positives finance group recommendation hybrid recommendation information extraction information retrieval information retrieval models information retrieval theory knn link prediction metasearch metrics multi-armed bandits multimedia retrieval news retrieval nlp non-random missing data novelty performance prediction personalization popularity probability ranking principle rank aggregation rank fusion recommender systems relation extraction semantic annotation semantic search semantics social networks web services
2019 |
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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. Poster |
2017 |
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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. Slides |