Author:
Castells Pablo,Hurley Neil J.,Vargas Saul
Reference90 articles.
1. Adamopoulos, P., Tuzhilin, A.: On unexpectedness in recommender systems: Or how to better expect the unexpected. ACM Transactions on Intelligent Systems and Technology 4(5), Special Section on Novelty and Diversity in Recommender Systems, 54:1–54-32 (2015)
2. Adomavicius, G., Kwon, Y.: Maximizing aggregate recommendation diversity: A graph-theoretic approach. In: Proceedings of the 1st ACM RecSys Workshop on Novelty and Diversity in Recommender Systems, DiveRS 2011, pp. 3–10 (2011)
3. Adomavicius, G., Kwon, Y.: Improving aggregate recommendation diversity using ranking-based techniques. IEEE Transactions on Knowledge and Data Engineering 24(5), 896–911 (2012)
4. Adomavicius, G., Kwon, Y.: Optimization-based approaches for maximizing aggregate recommendation diversity. INFORMS Journal on Computing 26(2), 351–369 (2014)
5. Adomavicius, G., Tuzhilin, A.: Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. IEEE Transactions on Knowledge and Data Engineering 17(6), 734–749 (2005)
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