Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Information Systems
Reference10 articles.
1. Adomavicius, G., & Tuzhilin, A. (2015). Context-aware recommender systems. In Recommender systems handbook (pp. 191–226). Springer US, Boston, MA.
https://doi.org/10.1007/978-1-4899-7637-6_6
.
2. Chakraborty, A., Ghosh, S., Ganguly, N., & Gummadi, K. P. (2019). Optimizing the recency-relevance-diversity trade-offs in non-personalized news recommendations. Information Retrieval Journal, 2, 1–29.
3. Clarke, C. L., Kolla, M., Cormack, G. V., Vechtomova, O., Ashkan, A., Büttcher, S., & MacKinnon, I. (2008). Novelty and diversity in information retrieval evaluation. In Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval-SIGIR ’08 (p. 659). ACM Press, New York, New York, USA.
https://doi.org/10.1145/1390334.1390446
,
http://portal.acm.org/citation.cfm?doid=1390334.1390446
.
4. Karlsen, R., Steen-Johnsen, K., Wollebæk, D., & Enjolras, B. (2017). Echo chamber and trench warfare dynamics in online debates. European Journal of Communication, 32(3), 257–273.
5. Lindner, A., Hall, M., Niemeyer, C., & Caton, S. (2015). BeWell: A sentiment aggregator for proactive community management work-in. In CHI’15 (pp. 1055–1060).
https://doi.org/10.1145/2702613.2732787
.
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