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【書籍紹介】基礎から学ぶ推薦システム - 情報技術で嗜好を予測する -
【論文紹介】Fighting Mainstream Bias in Recommender Systems via Local Fine Tuning
【論文紹介】Transformers4Rec: Bridging the Gap between NLP and Sequential / Session-Based Recommendation
【論文紹介】TFROM: A Two-sided Fairness-Aware Recommendation Model for Both Customers and Providers
【論文紹介】DGCN: Diversified Recommendation with Graph Convolutional Networks
【論文紹介】Empirical analysis of session-based recommendation algorithms
【論文紹介】Package Recommendation with Intra- and Inter-Package Attention Networks
【論文紹介】Next-item Recommendations in Short Sessions
【論文紹介】Do Loyal Users Enjoy Better Recommendations?: Understanding Recommender Accuracy from a Time Perspective
【論文紹介】Exploring the Impact of Temporal Bias in Point-of-Interest Recommendation
【論文紹介】Estimation of Fair Ranking Metrics with Incomplete Judgments
【論文紹介】CPFair: Personalized Consumer and Producer Fairness Re-ranking for Recommender Systems
【論文紹介】ProtoMF: Prototype-based Matrix Factorization for Effective and Explainable Recommendations
【論文紹介】Choice of Implicit Signal Matters: Accounting for User Aspirations in Podcast Recommendations
【論文紹介】Learning Explicit User Interest Boundary for Recommendation
【論文紹介】A Gain-Tuning Dynamic Negative Sampler for Recommendation
【論文紹介】Local Collaborative Autoencoders
【論文紹介】The Datasets Dilemma: How Much Do We Really Know About Recommendation Datasets?