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The first Dutch-Belgian Workshop on Recommender Systems
October 30, 2023
I have been advocating more ‘local’ initiatives to connect the regional recommender-systems communities for a long time (e.g. I am still hoping for a European RecSys Conference). As such, I am very glad to see the announcement of the “DBWRS“. The DBWRS is the first Dutch-Belgian Recommender Systems Workshop, taking place 14-15 December 2023 in Antwerp, Belgium. It’s organized by Lien Michiels, Annelien Smets, Jefrey Lijffijt, Bart Goethals, Jens Leysen, and Brett Binst. The submission deadline has passed already, the program is online, and registration is open.
In the digital age, information overload is common. Recommender systems aid users in navigating data. They’re widespread in e-commerce, social media, and entertainment, impacting how we find products, interact with content, and connect with others.
DBWRS promotes cross-disciplinary collaboration. The agenda covers topics like machine learning, user modeling, algorithm design, human-computer interaction, ethical aspects, and business implications of recommender systems. Through multidisciplinary insights, the aim is to understand how to build effective, responsible recommender systems that cater to individual user needs.
Whether a researcher, senior investigator, or industry practitioner, DBWRS offers a platform for engaging discussions, idea sharing, and forming collaborations to advance recommendation technology. The workshop will host experts from fields like computer science, data science, artificial intelligence, and more to discuss the latest advancements, challenges, and opportunities in this field.
Join us to explore recommender systems’ interdisciplinary nature, discover innovative approaches for enhanced user experiences, personalized decision-making, and contribute to the evolving digital recommendation landscape.
I am the founder of Recommender-Systems.com and head of the Intelligent Systems Group (ISG) at the University of Siegen, Germany https://isg.beel.org. We conduct research in recommender-systems (RecSys), personalization and information retrieval (IR) as well as on automated machine learning (AutoML), meta-learning and algorithm selection. Domains we are particularly interested in include smart places, eHealth, manufacturing (industry 4.0), mobility, visual computing, and digital libraries.
We founded or maintain, among others, LensKit-Auto, Darwin & Goliath, Mr. DLib, and Docear, each with thousand of users; we contributed to TensorFlow, JabRef and others; and we developed the first prototypes of automated recommender systems (AutoSurprise and Auto-CaseRec) and Federated Meta Learning (FMLearn Server and Client).