Publisher
Springer Science and Business Media LLC
Subject
Management of Technology and Innovation,Marketing,Computer Science Applications,Economics and Econometrics,Business and International Management
Reference100 articles.
1. Adomavicius, G., & Kwon, Y. (2014). Optimization-based approaches for maximizing aggregate recomme-ndation diversity. INFORMS Journal on Computing, 26(2), 351–369. https://doi.org/10.1287/ijoc.2013.0570.
2. Amrollahi, A. (2019). Burst the filter bubble: Towards an integrated tool. In proceedings of the 30th Australasian conference on information Systems (pp. 12-20). ACIS.
3. Amrollahi, A. (2021). A conceptual tool to eliminate filter bubbles in social networks. Australasian Journal of Information Systems, 25, 1–16. https://doi.org/10.3127/ajis.v25i0.2867.
4. Ashkan, A., Kveton, B., Berkovsky, S., & Wen, Z. (2015). Optimal greedy diversity for recommendation. In proceeding of the 24th international conference on artificial intelligence (pp. 1742-1748). IJCAI.
5. Bag, S., Ghadge, A., & Tiwari, M. K. (2019). An integrated recommender system for improved accuracy and aggregate diversity. Computers & Industrial Engineering, 130, 187–197. https://doi.org/10.1016/j.cie.2019.02.028.
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