Publications

Binst, B., Michiels, L., & Smets, A. (2025). What is Serendipity? An Interview Study to Conceptualize Experienced Serendipity in Recommender Systems. In Proceedings of the 33rd ACM Conference on User Modeling, Adaptation and Personalization. https://doi.org/10.48550/arXiv.2505.15440

Maes, U., Michiels, L., & Smets, A. (2025). Mitigating Misleadingness in LLM-Generated Natural Language Explanations for Recommender Systems: Ensuring Broad Truthfulness Through Factuality and Faithfulness. In Joint Proceedings of the ACM IUI 2025 Workshops co-located with the 30th Annual ACM Conference on Intelligent User Interfaces (IUI 2025) CEUR Workshop Proceedings. https://doi.org/https://axai.trx.li/papers/11.pdf

Smets, A., & Ballon, P. (Eds.). (Forthcoming 2025). Handbook of Platform Urbanism. Edward Elgar Publishing Ltd.

Ballon, P., & Smets, A. (Forthcoming 2025). Introduction to the Handbook of Platform Urbanism. In A. Smets & P. Ballon (Eds.), Handbook of Platform Urbanism. Edward Elgar Publishing Ltd.

Starke, A. D., Vrijenhoek, S., Michiels, L., Kruse, J., & Tintarev, N. (2025). Proceedings of the Second Workshop on the Normative Design and Evaluation of Recommender Systems (NORMalize 2024) co-located with the 18th ACM Conference on Recommender Systems (RecSys 2024). CEUR Workshop Proceedings, Vol. 3898. https://ceur-ws.org/Vol-3898/

Tam, B., Taelman, R., Rojas-Melendez, J., Colpaert, P. (2024). Optimizing Traversal Queries of Sensor Data Using a Rule-Based Reachability Approach, In proceedings of the 23rd International Semantic Web Conference (ISWC).

Tam, B., Taelman, R., Colpaert, P., & Verborgh, R. (2024). Opportunities for Shape‑Based Optimization of Link Traversal Queries. In Proceedings of the 16th Alberto Mendelzon International Workshop on Foundations of Data Management (AMW 2024). https://doi.org/10.48550/arXiv.2407.00998

Ranaivoson, H., Smets, A., & Ballon, P. (2024). Challenges and Opportunities for Recommender Systems in Media Markets. In U. Rohn, M. B. Rimscha, & T. Raats (Eds.), De Gruyter Handbook of Media Economics (pp. 215–228). De Gruyter.

Barraza‑Urbina, A., Brusilovsky, P., Cai, W., Falk, K., Goethals, B., Konstan, J. A., Porcaro, L., Smets, A., et al. (2024). Evaluating the Long‑Term Impact of Recommender Systems. In C. Bauer, A. Said, & E. Zangerle (Eds.), Evaluation Perspectives of Recommender Systems: Driving Research and Education (Dagstuhl Seminar 24211), 146–171. Schloss Dagstuhl. https://doi.org/10.4230/DagRep.14.5.58

Binst, B. (2024). How to Evaluate Serendipity in Recommender Systems: The Need for a Serendiptionnaire. In Proceedings of the 18th ACM Conference on Recommender Systems (pp. 1335–1341). https://doi.org/10.1145/3640457.3688017

Beel, J., Wegmeth, L., Michiels, L., & Schulz, S. (2024). Informed Dataset Selection with ‘Algorithm Performance Spaces’. In Proceedings of the 18th ACM Conference on Recommender Systems (pp. 1085–1090). ACM.

De Pauw, J., & Goethals, B. (2024). The Role of Unknown Interactions in Implicit Matrix Factorization: A Probabilistic View. In Proceedings of the 18th ACM Conference on Recommender Systems (pp. 219–227). https://doi.org/10.1145/3640457.3688100

Kruse, J., Michiels, L., Starke, A., Tintarev, N., & Vrijenhoek, S. (2024). NORMalize: A Tutorial on the Normative Design and Evaluation of Information Access Systems. In Proceedings of the 2024 ACM Conference on Human Information Interaction and Retrieval (CHIIR ’24) (pp. 422–424). https://doi.org/10.1145/3627508.3638319

Starke, A. D., Vrijenhoek, S., Michiels, L., Kruse, J., & Tintarev, N. (2024). NORMalize 2024: The Second Workshop on Normative Design and Evaluation of Recommender Systems. In Proceedings of the 18th ACM Conference on Recommender Systems (pp. 1242–1244). https://doi.org/10.1145/3640457.3687103

Michiels, L., Vannieuwenhuyze, J., Leysen, J., Verachtert, R., Smets, A., & Goethals, B. (2023). How Should We Measure Filter Bubbles? A Regression Model and Evidence for Online News. In Proceedings of the 17th ACM Conference on Recommender Systems. https://doi.org/10.1145/3604915.3608805

Vrijenhoek, S., Michiels, L., Kruse, J., Starke, A., Viader Guerrero, J. V., & Tintarev, N. (2023). NORMalize: The First Workshop on Normative Design and Evaluation of Recommender Systems. In Proceedings of the 17th ACM Conference on Recommender Systems (pp. 1252–1254). https://doi.org/10.1145/3604915.3608757

Bauer, C., Carterette, B., Ferro, N., Fuhr, N., Beel, J., Breuer, T., Clarke, C. L. A., et al. (2023). Report on the Dagstuhl Seminar on Frontiers of Information Access Experimentation for Research and Education. ACM SIGIR Forum, 57(1), 1–28. https://doi.org/10.1145/3636341.3636351

Binst, B., Vandenbroucke, H.,  Li, D., Puskas, I., Van der Elst, P. & Smets, A. (2023). Towards a Pragmatic Approach for Studying Normative Recommender Systems: Exploring Power Dynamics in Digital Platform Markets. The First Workshop on Normative Design and Evaluation of Recommender Systems.

Michiels, L., Verachtert, R., Ferraro, A., Falk, K., & Goethals, B. (2023). A Framework and Toolkit for Testing the Correctness of Recommendation Algorithms. ACM Transactions on Recommender Systems. https://dl.acm.org/doi/pdf/10.1145/3591109

Smets, A. (2023). Designing for serendipity: a means or an end?. Journal of Documentation, 79(3), 589-607. https://doi.org/10.1108/JD-12-2021-0234

Smets, A., Michiels, L., Bogers, T., & Björneborn, L. (2022). Serendipity in Recommender Systems Beyond the Algorithm: A Feature Repository and Experimental Design. In 16th ACM Conference on Recommender Systems. CEUR Workshop Proceedings (pp. 44-66). https://ceur-ws.org/Vol-3222/paper4.pdf

Michiels, L., Leysen, J., Smets, A., & Goethals, B. (2022). What Are Filter Bubbles Really? A Review of the Conceptual and Empirical Work. In Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (pp. 274-279). https://doi.org/10.1145/3511047.3538028

Michiels, L., Verachtert, R., & Goethals, B. (2022). RecPack: An (other) Experimentation Toolkit for Top-N Recommendation using Implicit Feedback Data. In Proceedings of the 16th ACM Conference on Recommender Systems (pp. 648-651). https://doi.org/10.1145/3523227.3551472

Vannieuwenhuyze, J., Smets, A., Gebert, M., & Ballon, P. (2022). Methodological Analysis of Personalization in Urban Recommender Systems by Distance Measures. Telematics and Informatics, 71.  https://doi.org/10.1016/j.tele.2022.101818  

De Pauw, J., Ruymbeek, K., & Goethals, B. (2022). Who Do You Think I Am? Interactive User Modelling with Item Metadata. In Proceedings of the 16th ACM Conference on Recommender Systems (pp. 640–643). https://doi.org/10.1145/3523227.3551470

Smets, A., & Ballon, P. (2020). Efficiënt maar suboptimaal: onze digitale communicatie heeft nood aan serendipiteit. In Post Viraal naar een Nieuw Normaal (pp. 209-216). VUBPress. 

Smets, A., Ballon, P., & Walravens, N. (2021). Mediated by Code: Unpacking Algorithmic Curation of Urban Experiences. Media and Communication, 9(4), 250-259. https://doi.org/10.17645/mac.v9i4.4086 

Delva, H., Smets, A., Colpaert, P., Ballon, P., & Verborgh, R. (2020). Using Regions of Interest for Personalized Route Planning. In Proceedings of the 2nd International Workshop on Semantics for Transport (pp. 47-52). Springer. 
https://link.springer.com/chapter/10.1007/978-3-030-65665-2_5

Smets, A., Montero, E., & Ballon, P. (2019). Does the bubble go beyond? An exploration of the urban filter bubble. In The 1st Workshop on the Impact of Recommender Systems with ACM RecSys 2019 (Vol. 2462).  CEUR Workshop Proceedings. http://ceur-ws.org/Vol-2462/paper3.pdf