ACM RecSys

@acmrecsysAnalyzed

Artificial intelligenceMachine learningResearch & academiarecommender-systemsartificial-intelligencemachine-learningdata-scienceresearch
Open on YouTube

Audience and activity

Subscribers7.6K
Views per video383median of the last 30
Views per subscriber0.05how many actually watch
Comments per video0median
Uploads per month22.0
Last upload1.0y ago2025-10-02
Total views391K
Total videos643
Long-form / Shorts55% / 0%

Counts come from the YouTube Data API and are refreshed regularly; medians are computed from the channel's last 30 videos.

What ACM RecSys makes

Topics recommender-systems, artificial-intelligence, machine-learning, data-science, research

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. Recommendation is a particular form of information filtering, that exploits past behaviors and user similarities to generate a list of information items that is personally tailored to an end-user’s preferences. As RecSys brings together the main international research groups working on recommender systems, along with many of the world’s leading e-commerce companies, it has become the most important annual conference for the presentation and discussion of recommender systems research.

Features other people

Recent videos

TitlePublishedViewsLength
Keynote Xavier Amatriain2025-10-023.5K58 min
NLGCL: Naturally Existing Neighbor Layers Graph Contrastive Learning for Recommendation2025-10-0238311 min
LLM-RecG: A Semantic Bias-Aware Framework for Zero-Shot Sequential Recommendation2025-10-0248712 min
Leave No One Behind: Fairness-Aware Cross-Domain Recommender Systems for Non-Overlapping Users2025-10-023209 min
Lasso: Large Language Model-based User Simulator for Cross-Domain Recommendation2025-10-022677 min
Hierarchical Graph Information Bottleneck for Multi-Behavior Recommendation2025-10-0222811 min
Enhancing Transferability and Consistency in Cross-Domain Recommendations via Supervised Disentangle2025-10-022019 min
You Don’t Bring Me Flowers: Mitigating Unwanted Recommendations Through Conformal Risk Control2025-10-0241711 min
Mapping Stakeholder Needs to Multi-Sided Fairness in Candidate Recommendation for Algorithmic Hiring2025-10-021249 min
Integrating Individual and Group Fairness for Recommender Systems through Social Choice2025-10-0216410 min

Contact ACM RecSys

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YouTube youtube.com/@acmrecsys

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