Reimagining RecSys Research and Practice

More workshops at ACM Conference on Recommender Systems 2026

• Interdisciplinarity of Recommender Systems — Brings interdisciplinary perspectives to recommender systems research.
• Context-Aware Recommender Systems — Focuses on modeling and exploiting context in recommendation.
• Causality and Sequential Decision-Making for RecSys — Covers causal inference, counterfactual evaluation, and sequential decision making in recommendation.
• Data Quality-Aware Multimodal Recommendation — Addresses data quality in multimodal recommender systems.
• Rethinking Research Assessment in RecSys — Examines methodology and research assessment practices in recommender systems research.
• Agentic and Generative AI for E-Commerce — Explores generative and agentic AI in e-commerce recommendation and search.
• Interfaces and Human Decision Making for RecSys — Examines user interfaces and human decision making in recommender systems.
• Music Recommender Systems — Dedicated to recommender systems for music streaming and discovery.
• Online Adaptive Recommender Systems — Covers recommender systems that adapt online to changing user behavior and content.
• RecSys for Sustainability and Social Good — Focuses on recommenders that advance sustainability and social good.
• Recommender Systems for Human Resources — Focuses on recommenders for recruitment, job matching, and human resources.
• Temporal Reasoning in Recommendation — Covers time-aware and temporal reasoning approaches in recommendation.
• Recommenders in Tourism — Covers recommender systems for travel and tourism.
• Unified Search and Recommendation — Examines unified models and systems spanning search and recommendation.