大模型驱动的推荐前沿进展

Large Language Models for Recommendation: Progresses and Future DirectionFuli Feng USTCThanks to Jizhi Zhang, Keqin Bao, Yang Zhang, Wenjie Wang, Xiangnan He1YSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024Background of RecSys2qInformation explosion era•E-commerce: 12 million items in Amazon.•Social networks: 2.8 billion users in Facebook.•Content sharing platforms: 720,000 hours videos uploaded to Youtube per day； 35 million videos posted on TikTok dailyqRecommender systemInformation seekingvia user history feedbackRecommendationImages from: Deep neural networks for youtube recommendationsYSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024YSSNLP2024Background of RecSys3RecommendationsInteractionsUser feedbackRecommenderTrainingInferenceSystem sideUser sideItemdatabaseUserqWorkflow of Recommender System (1) Train recommender on collected interaction data to capture user preferences.(2) Recommender genrates recommend