We announce LensKit-Auto 0.1.1, our open-source AutoRecSys library built on the Python LensKit recommender system framework. What is LensKit-Auto? Originally introduced as a Demo paper at the 17th ACM Conference on Recommender Systems (RecSys 2023), LensKit-Auto simplifies the labor-intensive parts of recommender systems research by automating the entire recommender systems Read more…
Zusammenfassung: Eine Kundin kauft Babygrieß bei Rossmann, meint ranzigen Geruch wahrzunehmen und reklamiert. In der Filiale wird die Kundin nach langer Diskussion des Ladens verwiesen und die Rücknahme mit Argumenten verweigert, die später vor Gericht keinen Bestand haben werden. Ich biete der Kundin Unterstützung bei der Durchsetzung Ihrer Rechte an, Read more…
We are excited to share that our PhD student, Tobias Vente, presented our research paper, “APS Explorer: Navigating Algorithm Performance Spaces for Informed Dataset Selection”, at the ACM RecSys 2025 conference held at the O2 Universum Convention Center in Prague, Czechia The Problem: Why RecSys Needs Better Dataset Selection An analysis of all full papers accepted at Read more…
Alan Said, chair of the ACM RecSys steering committee, just announced that the ACM Recommender Systems Conference (RecSys) 2027 will take place in Hawaiʻi. I, Joeran Beel, will serve as General Co-Chair together with Christine Bauer and Bamshad Mobasher. Dates (likely late September) and venue will be announced, at the Read more…
Lukas Wegmeth & Tobias Vente, both fourth-year Ph.D. students at the Intelligent Systems Group, were invited to SFI MediaFutures in Bergen, Norway, to give a talk on the sustainability of Recommender Systems on April 4th, 2025. Prof. Sole Pera also gave an invited talk on responsible Recommender Systems on the Read more…
PhD students Lukas Wegmeth and Tobias Vente had the opportunity to visit Tsinghua University in Beijing, China, for a month-long research visit with Professor Min Zhang, a leading expert in recommender systems and information retrieval. Professor Min Zhang is a distinguished professor in the Department of Computer Science at Tsinghua Read more…
As part of his research semester, Prof. Beel visited Prof. Min Zhang at Tsinghua University. Professor Min Zhang is a professor in the Department of Computer Science at Tsinghua University and an influential researcher in information retrieval and recommender systems. She serves as the Editor-in-Chief of ACM Transactions on Information Read more…
Prof. Joeran Beel visited Prof. Li Chen at Baptist University Hong Kong (HKBU) as part of his research semester. During his visit, Prof. Beel delivered a seminar on sustainable recommender systems, attended the HKBU-NVIDIA Joint Symposium 2025, and collaborated with Prof. Chen on the future development of the ACM Transactions Read more…
Abstract As recommender systems become increasingly prevalent, the environmental impact and energy efficiency of training these large-scale models have come under scrutiny. This paper investigates the potential for energy-efficient algorithm performance by optimizing dataset sizes through downsampling techniques. We conducted experiments on the MovieLens 100K, 1M, 10M and Amazon Toys Read more…
Accepted for publication at the International Conference on Artificial Intelligence and Machine Learning Research (CAIMLR). The PDF is available here. Feel free to also read the original proposal that led to the current publication. Abstract In this paper, we present e-fold cross-validation, an energy-efficient alternative to k-fold, which dynamically adjusts Read more…
Accepted for publication as late-breaking-result (LBR) at the 18th ACM Conference on Recommender Systems. Read the article as PDF here. Abstract When designing recommender-systems experiments, a key question that has been largely overlooked is the choice of datasets. In a brief survey of ACM RecSys papers, we found that authors Read more…
Full pre-print as PDF: https://arxiv.org/abs/2408.08203 Abstract As global warming soars, the need to assess the environmental impact of research is becoming increasingly urgent. Despite this, few recommender systems research papers address their environmental impact. In this study, we estimate the ecological impact of recommender systems research by reproducing typical experimental Read more…
We proudly announce that the Department of Electrical Engineering and Computer Science at the University of Siegen and the Department of Applied Information Technology at the University of Gothenburg have signed an Erasmus agreement. The agreement will support exchanges and research visits of Master’s students, researchers (e.g. PhD students), and Read more…
Tobias spent two weeks with Bart Goethels and his team at the ADReM Data Lab at the University of Antwerp. He worked on novel recommender system algorithms incorporating ensembling techniques during this time. Located within the Department of Mathematics and Computer Science, the Adrem Data Lab comprises four faculty members, Read more…
Recently, we were delighted to learn that our paper “Revealing the Hidden Impact of Top-N Metrics on Optimization in Recommender Systems” was accepted for the “Full Paper” track at the ECIR 2024. The paper, co-authored by members of our chair, the Intelligent Systems Group, will be presented by one of Read more…
The Germany Academic Exchange Service (DAAD – Deutscher Akademischer Austauschdienst) invited its alumni to Berlin to discuss recent advances in generative artificial intelligence. Dr. Holger Finken, Cordula Behrsing and Jana Zettler organized the event. Prof. Dr. Ute Schmid held the opening keynote on trustworthy AI. Prof. Joeran Beel also attended Read more…
Our Ph.D. students, Tobias Vente, and Lukas Wegmeth, will attend the ACM RecSys 2023 conference in Singapore to present their latest work on Automated Recommender Systems (AutoRecSys) with four papers: two in the Doctoral Symposium, one in the PERSPECTIVES 2023 Workshop, and one in the Demo track. We already posted Read more…
The ACM RecSys 2023 Doctoral Symposium Chairs accepted the extended abstracts that Tobias Vente and Lukas Wegmeth submitted. Abstracts will be presented by their authors and discussed with the chairs and other students at the conference. The extended abstract was limited to eight pages, and an unusually high amount of Read more…
We are grateful for the opportunity to present some of our recent work at the ISG with two posters at the COSEAL Workshop 2023 at Sorbonne University in Paris. The COnfiguration and SElection of ALgorithms (COSEAL) network of researchers regularly meets to discuss recent advances in the field of algorithm Read more…
At the end of last year, we had the pleasure of presenting our publication of Lennart Purucker‘s Master thesis at the 22nd IEEE International Conference on Data Mining (ICDM) in Florida, USA! Lennart worked on Meta-Learning for Subgroup Discovery during his Master’s thesis at the RWTH Aachen University. As part Read more…
We are happy to announce that the ISG Siegen is involved in the organization of the AutoML Conference 2023! Lennart Purucker, one of our Ph.D. students, is the Reproducibility Chair for the AutoML Conference 2023. The Reproducibility Chair is a newly established chair with the goal of enabling and observing Read more…
Update 2023-05: The report is now available on arXiv.org. Prof. Beel was invited to attend the Dagstuhl seminar about ‘Frontiers of Information Access Experimentation for Research and Education‘. The seminar took place from January 15 to January 20, 2023 in Schloss Dagstuhl, and was organized by Christine Bauer (Utrecht University, Read more…