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 link prediction machine learning metasearch metrics multi-armed bandits multimedia retrieval news retrieval nlp non-random missing data novelty performance prediction personalization popularity query aspect rank aggregation rank fusion recommender systems relation extraction semantic annotation semantic search semantics social networks time web search web services
|D. Valcarce, A. Bellogín, J. Parapar, P. Castells. On the Robustness and Discriminative Power of IR Metrics for Top-N Recommendation. 12th ACM Conference on Recommender Systems (RecSys 2018). Vancouver, Canada, October 2018, pp. 260-268.|
R. Cañamares, P. Castells.
From the PRP to the Low Prior Discovery Recall Principle for Recommender Systems.
41st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2018). Ann Arbor, Michigan, USA. July 2018, pp. 1081-1084.
|A. Bellogín, P. Castells, I. Cantador. Precision-Oriented Evaluation of Recommender Systems: An Algorithmic Comparison. 5th ACM Conference on Recommender Systems (RecSys 2011). Chicago, Illinois, October 2011, pp. 333-336.|
S. Vargas, P. Castells.
Rank and Relevance in Novelty and Diversity Metrics for Recommender Systems.
5th ACM Conference on Recommender Systems (RecSys 2011). Chicago, Illinois, October 2011, pp. 109-116.
S. Vargas, P. Castells, D. Vallet.
Intent-Oriented Diversity in Recommender Systems.
34th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2011), Poster Session. Beijing, China, July 2011, pp. 1211-1212.
|P. Castells, S. Vargas, J. Wang. Novelty and Diversity Metrics for Recommender Systems: Choice, Discovery and Relevance. International Workshop on Diversity in Document Retrieval (DDR 2011) at the 33rd European Conference on Information Retrieval (ECIR 2011). Dublin, Ireland, April 2011.|