The DOI matches its Crossref record; 99 of the 99 references it cites were found in a registry or an index.
Serendipity in Recommender Systems: A Systematic Literature Review
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“Therefore, to balance out familiarity, diversity and novelty, it is necessary to consider the inclusion of serendipitous recommendations that are unexpected but still can be relevant (Ziarani and Ravanmehr 2021).”
From AdaptUI: A Framework for the development of Adaptive User Interfaces in Smart Product-Service Systems (2024) · cites this paper as Ziarani and Ravanmehr 2021
Citations
Cites
Item-based collaborative filtering recommendation algorithms
Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2001) · Proceedings of the 10th international conference on World Wide Web · doi:10.1145/371920.372071 · Cited by 9,135
Neural Collaborative Filtering
He, X., Liao, L., Zhang, H., Nie, L., Hu, X., & Chua, T. (2017) · International World Wide Web Conference (WWW) · doi:10.1145/3038912.3052569 · Cited by 7,385
Systematic Literature Reviews in Software Engineering—A Systematic Literature Review
Kitchenham, B., Pearl Brereton, O., Budgen, D., Turner, M., Bailey, J., & Linkman, S. (2009) · Information and Software Technology · doi:10.1016/j.infsof.2008.09.009 · Cited by 4,537
The psychology of curiosity: A review and reinterpretation.
Loewenstein, G. (1994) · Psychological Bulletin · doi:10.1037/0033-2909.116.1.75 · Cited by 2,738
Guidelines for conducting systematic mapping studies in software engineering: An update
Petersen, K., Vakkalanka, S., & Kuzniarz, L. (2015) · Information and Software Technology · doi:10.1016/j.infsof.2015.03.007 · Cited by 2,669
Recommender Systems: Introduction and Challenges
Ricci, F., Rokach, L., & Shapira, B. (2015) · Recommender Systems Handbook · doi:10.1007/978-1-4899-7637-6_1 · Cited by 894
Kaminskas, M., & Bridge, D. (2017) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/2926720 · Cited by 465
A systematic review and taxonomy of explanations in decision support and recommender systems
Nunes, I., & Jannach, D. (2017) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-017-9195-0 · Cited by 416
A survey of serendipity in recommender systems
Kotkov, D., Wang, S., & Veijalainen, J. (2016) · Knowledge-Based Systems · doi:10.1016/j.knosys.2016.08.014 · Cited by 360
News recommender systems – Survey and roads ahead
Karimi, M., Jannach, D., & Jugovac, M. (2018) · Information Processing & Management · doi:10.1016/j.ipm.2018.04.008 · Cited by 337
Cited by
Sorted by citations
A survey on popularity bias in recommender systems
Klimashevskaia, A., Jannach, D., Elahi, M., & Trattner, C. (2024) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-024-09406-0 · Cited by 223
Benefits of Diverse News Recommendations for Democracy: A User Study
Heitz, L., Lischka, J. A., Birrer, A., Paudel, B., Tolmeijer, S., Laugwitz, L. L., & Bernstein, A. (2022) · Digital Journalism · doi:10.1080/21670811.2021.2021804 · Cited by 100
Mattis, N. M., Masur, P. K., Möller, J. E., & van Atteveldt, W. (2022) · New Media & Society · doi:10.1177/14614448221104413 · Cited by 78
Recommender systems for sustainability: overview and research issues
Felfernig, A., Wundara, M., Tran, T. N. T., Erdeniz, S. P., Lubos, S., Mansi, M. E., Garber, D., & Le, V.-M. (2023) · Frontiers in Big Data · doi:10.3389/fdata.2023.1284511 · Cited by 66
Knowledge-based recommender systems: overview and research directions
Uta, M., Felfernig, A., Le, V.-M., Tran, T. N. T., Garber, D., Lubos, S., & Burgstaller, T. (2024) · Frontiers in Big Data · doi:10.3389/fdata.2024.1304439 · Cited by 41
Metadata
- Authors
- Ziarani, R. J., & Ravanmehr, R.
- Affiliations
- Islamic Azad University, Tehran (IR)
- Corresponding author
- Ravanmehr, Reza
- ORCID
- Ravanmehr, Reza
- Venue
- Journal of Computer Science and Technology
- Published
- 2021-03-31
- Volume
- 36
- Issue
- 2
- Pages
- 375-396
- ISSN
- 1000-9000 (ISSN-L)
- 1860-4749
- OpenAlex
- W3154445493
- Cited by
- 123
- References
- 99
- Citations by year
- 2026: 19 · 2025: 27 · 2024: 27 · 2023: 29 · 2022: 14 · 2021: 7
- FWCI
- 2.94
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Computer Science and Technology (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Social Sciences › Decision Sciences › Management Science and Operations Research › Advanced Bandit Algorithms Research
- Keywords
- serendipity, recommender systems, serendipitous recommendation, novelty, recommendation diversity, recommendation relevance, recommendation evaluation
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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