3 RecSys Workshops and RecSys KDD Cup at the 2023 KDD conference
KDD is a premier conference and KDD 2023 is also interesting for recommender-systems researchers as it features 3 recommender-systems workshops. Namely,
EvalRS2023, A Well-Rounded Evaluation of Recommender Systems. The Second Edition of the workshop on well-rounding the evaluation of recommender systems, covering fairness, robustness and trustworthiness.
OARS 2023, the workshop on online and adaptive recommender systems (OARS) will serve as a platform for publication and discussion of OARS. This workshop will bring together practitioners and researchers from academia and industry to discuss the challenges and approaches to implement OARS algorithms and systems, and improve user experiences by better modeling and responding to user intent.
AdKDD 2023: The AdKDD workshops held in conjunction with KDD conferences in the past years (2017-2022) continue to generate interest from academia and industry–as one of the top venues specifically for advertising research. We believe this is a unique forum for folks interested in aspects of digital advertising to get together, exchange notes and get a pulse for the state of the art, especially in the industry.
And, as if that’s not enough, the KDD Cup 2023 also relates to recommender systems, with a Shopping Session Dataset by Amazon.
PodRecs@RecSys2020: Workshop on Podcast Recommendations
ORSUM@RecSys2020: 3rd Workshop on Online Recommender Systems and User Modeling
CARS@RecSys2020: Workshop on Context-Aware Recommender Systems
About The Author
Joeran Beel
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).