RecSys

Our multidisciplinary group works on recommender systems at Tampere University. We focus on various problems, such as:

Recommendations for groups // Sequential recommendations // Fairness, diversity and transparency in recommendations and rankings // Explanations and why-not questions in recommender systems

As well as complementary topics related to the problem of entity resolution, like:

Progressive entity resolution // Iterative blocking and matching // Fairness and diversity in entity resolution // Explanations in entity resolution

We participate in multi-disciplinary research, building on computer science, data science, internet research, social sciences. We aim to design for more ethically sustainable information and communications technology.

Contact: konstantinos.stefanidis@tuni.fi

RecSys is part of the Faculty of Information Technology and Communication Sciences (ITC) of the Tampere University.

[Organization] EDBT/ICDT 2026: International Conference on Extending Database Technology & International Conference on Database Theory, Tampere, Finland, 2026.

[Organization] ADBIS 2025: European Conference on Advances in Databases and Information Systems, Tampere, Finland, 2025.

[August 2024] E. Skenderi, J. Huhtamäki, S-M. Laaksonen and K. Stefanidis. INCEPT: A Framework for Duplicate Posts Classification with Combined Text Representations. ACM Transactions on the Web, Vol. 18, No. 3, 2024. [Link]

[May 2024] H-M. Attolou, K. Tzompanaki, K. Stefanidis and D. Kotzinos. Why-Not Explainable Graph Recommender. Proceedings of ICDE 2024. [Local copy]

[February 2023] M. Stratigi, E. Pitoura and K. Stefanidis. SQUIRREL: A Framework for Sequential Group Recommendations through Reinforcement Learning. Information Systems, 2022, Springer. [Local copy]

[October 2021] E. Pitoura, K. Stefanidis and G. Koutrika. Fairness in Rankings and Recommendations: An Overview. The VLDB Journal, 2021, Springer. [Local copy]