Overview
The ACM Recommender Systems conference (RecSys) is the premier international forum for the presentation of new research results, systems, and techniques in the broad field of recommender systems. RecSys brings together the major international research groups working on recommender systems, along with many of the world’s leading companies active in e-commerce and other adjacent domains.
Amazon organizing committee members
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Max HarperGeneral co-chair
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General co-chair
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Local co-chair
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Olivier JeunenWeb co-chair
Accepted publications
Workshops
RecSys 2022 Workshop: CONSEQUENCES – Causality, Counterfactuals and Sequential Decision-Making
Unknown date
The CONSEQUENCES+REVEAL workshop is an in-person event co-located with the Sixteenth ACM Conference on Recommender Systems in Seattle, WA, USA.
Amazon organizer: Olivier Jeunen
Website: https://sites.google.com/view/consequences2022
Amazon organizer: Olivier Jeunen
Website: https://sites.google.com/view/consequences2022
Recsys 2022 Workshop on Knowledge-aware and Conversational Recommender Systems
September 23
Recsys 2022 Workshop on Multi-Objective Recommender Systems
September 23
Recsys 2022 Workshop on Online Recommender Systems and User Modeling
September 23
The objective of this workshop is to foster contributions and bring together a growing community of researchers and practitioners interested in online, adaptive approaches to user modeling, recommendation and personalization, as well as other related tasks, such as evaluation, reproducibility, privacy and explainability.
Amazon keynote speaker: Eugene Yan
Amazon program committee: Olivier Jeunen
Website: https://orsum.inesctec.pt/orsum2022
Amazon keynote speaker: Eugene Yan
Amazon program committee: Olivier Jeunen
Website: https://orsum.inesctec.pt/orsum2022
Related content
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March 21, 2023Tailoring neighborhood sizes and sampling probability to nodes’ degree of connectivity improves the utility of graph-neural-network embeddings by as much as 230%.
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March 14, 2023Ren Zhang and her team tackle the interesting science challenges behind surfacing the most relevant offerings.
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February 09, 2023The collaboration includes Amazon funding for faculty research projects, with an initial focus on machine learning and natural-language processing.
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October 11, 2022Dual embeddings of each node, as both source and target, and a novel loss function enable 30% to 160% improvements over predecessors.