ACM RecSys 2026 Recap: Trends, a Paper Explorer & My Reading List
A data-driven recap of ACM RecSys 2026: 20 years of conference trends, the LLM turn in the papers, a tool to explore the proceedings, and...
Read more βRecommendation algorithms, evaluation metrics, and personalization techniques
A data-driven recap of ACM RecSys 2026: 20 years of conference trends, the LLM turn in the papers, a tool to explore the proceedings, and...
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Key highlights from RecSys 2024 including advances in matrix factorization, LLM integration, and the latest research from Netflix, Spotify, and GroupLens.
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A comprehensive overview of matrix factorization techniques for recommender systems, from SVD to deep learning approaches, with practical implementation tips.
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A comprehensive guide to designing recommender systems in 2024, covering core features, design principles, and practical implementation strategies.
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Comprehensive recap of RecSys 2023 covering industry practices, reproducibility research, new datasets, transformers in recommendations, and practical insights from Netflix, BBC, and Pinterest.
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Explore fallback strategies and serving rules in recommender systems. Learn how these underestimated pillars ensure reliable predictions in production environments.
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Hello, this is autumn and who says autumn says Recsys time, and this year Seattle was the place to be. I attended digitally to the...
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Explore Surprise, a Python scikit package for building recommender systems on explicit ratings. Learn collaborative filtering and two-stage recommender implementations.
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Once again, I attended (virtually) this year with some of my colleagues at RecSys 2021 in Amsterdam. In this article, I will recap exciting papers...
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I focused on this topic for the past three years at Ubisoft, but I never found suitable datasets to use for experiments on my blog...
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In this article, there will be a description on the Recsys conference that happened in September 2020 virtually (Thanks Ubisoft to have offer me the...
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In this article, there will be an introduction to the Neo4j graph database, leverage the technology for analytics and recommendation purposes.
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