Serendipity in Recommender Systems: A Systematic Literature Review

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

Diversity, Serendipity, Novelty, and Coverage: A Survey and Empirical Analysis of Beyond-Accuracy Objectives in Recommender Systems

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

Optimizing Reachability in Graph-Based Recommender Systems

Martínez, A., Cinus, F., Bonchi, F., & Vitria, J. M. (2025) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3744658

THE IMPACT OF THE IT AFFORDANCES OF LIVE STREAMING ON CONSUMER’S IMPULSIVE BUYING TENDENCY

Luo, H., & Dong, X. (2025) · The EUrASEANs journal on global socio-economic dynamics · doi:10.35678/2539-5645.4(53).2025.220-231 · Cited by 1

Investigating the Relationship Between User Preferences, Previous Ratings and User Judgments Related to Serendipity

Hertz, A., Kuflik, T., & Tuval, N. (2025) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2025.2546044

Determinants of Users' Chance-Seeking Behavior in Search-Based Recommendation

Ninomiya, Y., Sone, Y., Miwa, K., Sumi, Y., Nakanishi, R., Mitsuda, E., Sato, K., & Odashima, T. (2025) · ACM Conference on Recommender Systems (RecSys) · doi:10.1145/3705328.3748019

Exploring the Potential of Sound Leakage for Sharing Music

Aoki, H., Miyashita, H., & Nishimoto, K. (2025) · Procedia Computer Science · doi:10.1016/j.procs.2025.09.474

A Universal Framework for Offline Serendipity Evaluation in Recommender Systems via Large Language Models

Tokutake, Y., Okamoto, K., Harada, K., Shibata, A., & Karube, K. (2025) · ACM International Conference on Information and Knowledge Management (CIKM) · doi:10.1145/3746252.3760911 · Cited by 2

Maximizing Diverse Information Exposure in Content-Based Social Networks

Colin, J., & Maniu, S. (2025) · Lecture notes in computer science · doi:10.1007/978-3-662-72449-1_1

Glücklicher Zufall durch Digitalisierung (ortsgebundener) Gemeinschaften: Eine Fallstudie

Reh, S., & Engelhardt, C. (2025) · Springer eBooks · doi:10.1007/978-3-662-72004-2_15

Shadow baning: między „ministerstwem prawdy”, „tajną policją” algorytmiczną a pozyskiwaniem wiedzy o użytkownikach

Kreft, J. (2025) · Roczniki Kulturoznawcze · doi:10.18290/rkult25164.2 · Cited by 1

Enhancing Serendipity by Incorporating User Control of Social Information in a Recommender System

Jeon, G., Hong, J., Kim, S., & Lee, S. (2026) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2026.2619625

User Fairness in Recommender Systems Using Beyond-Accuracy Basket Quality Metrics

Bhaumik, D., Dey, D., Bril, M. T., & Stoica, V. (2026) · Communications in computer and information science · doi:10.1007/978-3-032-15638-9_17

Deep Natural Language Processing for User Representation

de Gabriac, C. G. D. F. (2021) · theses.fr (ABES) · doi:10.70675/f1d99786zd4d3z4d46z9b86z5de95a2b3290

Adaptive weighting-based hybrid recommender system: self-learning adaptive recommendation (SL-ARec)

Çakır, M. E., Çetinkaya, Z., Horasan, F., & Yurttakal, A. H. (2026) · PeerJ Computer Science · doi:10.7717/peerj-cs.3856 · Cited by 1

How AI Driven Recommendations Shape Purchase Intention in Short Video Commerce on E-Commerce Marketplaces: Evidence from the Mekong Delta, Vietnam

Tran, H. M. N., Que, A. P. N., & Nguyen, T. T. (2026) · International Conference on Knowledge Engineering and Communication Systems (ICKECS) · doi:10.1109/ickecs70176.2026.11527869

Enhancement of Content-Based Recommender Systems using Particle Swarm Optimization to Reduce Over-SpecializationPreprint

Purnomo, H. D., Christioko, B. V., Kristianto, B., & Sembiring, I. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.6962540

Improving Recommendation Serendipity by Chain-of-Thought Prompting in Large Language Models

Zheng, Q., Wu, H., Chen, H., Liu, Y., Xiao, B., Zhong, G., Hu, Y., & Wang, Z. (2026) · International Conference on Artificial Intelligence and Materials (ICAIM) · doi:10.1109/icaim69488.2026.11601833

Music Was My First Love: Biographic Resonance Makes Everyday Music Listening Meaningful

Dietrich, F., Ernst, A., Rohr, B., Scharkow, M., & Reinecke, L. (2026) · Communication Research · doi:10.1177/00936502261468400

The refined interaction value framework: advancing value co-creation in human–AI service systems in the AI-era

Wang, E. J., Berthon, P. R., & John, J. (2026) · Journal of Services Marketing · doi:10.1108/jsm-12-2025-0888

A Survey of Causal Learning in Graph-Based Recommender Systems

Yu, D., Li, Q., Soundararaj, B., Pettit, C. J., & Xu, G. (2026) · ACM Computing Surveys · doi:10.1145/3840748

Marketing communications in the age of AI: An S-O-R framework of how algorithmic recommendations shape consumer engagement and sustainable choices

Khan, I. A., Ausaf, A., & Khan, S. (2026) · Journal of Marketing Communications · doi:10.1080/13527266.2026.2725008

Synchronistic Experience as Salience Alignment in Biosemiotic Feedback Systems

McCoss, A. M. (2026) · Biosemiotics · doi:10.1007/s12304-026-09663-z

ALGORITHMIC HOMOGENIZATION AND THE "ECHO CHAMBER 2.0": QUANTIFYING CULTURAL STAGNATION IN AUTOMATED MEDIA ENVIRONMENTS

Bhatia, P. S., Singh, J., & Kumar, A. (2026) · ShodhKosh Journal of Visual and Performing Arts · doi:10.29121/shodhkosh.v7.i2.2026.9244

Recommender Systems Evaluation

Bellogín, A., & Said, A. (2026) · Springer eBooks · doi:10.1007/978-1-4614-7163-9_110162-2

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

Evaluating the Quality of Recommendation System by Using Serendipity Measure

Dorjmaa, T., & Shin, T. (2019) · Journal of Intelligence and Information Systems · doi:10.13088/jiis.2019.25.4.089 · Cited by 2

Computational Serendipitous Recommender System Frameworks: A Literature Survey

Abbas, F., & Niu, X. (2019) · IEEE/ACS International Conference on Computer Systems and Applications (AICCSA) · doi:10.1109/aiccsa47632.2019.9035339 · Cited by 14

A Serendipity-Oriented Greedy Algorithm for Recommendations

Kotkov, D., Veijalainen, J., & Wang, S. (2017) · International Conference on Web Information Systems and Technologies · doi:10.5220/0006232800320040 · Cited by 13

Challenges of Serendipity in Recommender Systems

Kotkov, D., Veijalainen, J., & Wang, S. (2016) · International Conference on Web Information Systems and Technologies · doi:10.5220/0005879802510256 · Cited by 78