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微信添加深蓝学院-叶子（微信号：shenlanyez），备注“52篇论文”，即可直接领取已打包的资料集注：数字表示引用量 1. 1012-Ontological user profiling in recommender systems.pdf 2. 1031-Deep Neural Networks for YouTube Recommendations.pdf 3. 1060-Internet Recommendation Systems.pdf 4. 1072-Trust in recommender systems.pdf 5. 1086-Being accurate is not enough： how accuracy metrics have hurt recommender systems.pdf 6. 1088- Collaborative Filtering Recommender Systems.pdf 7. 1100-Advances in Collaborative Filtering.pdf 8. 1111-Method, system and personalized web content manager responsive to browser viewers' psychological preferences, behavioral responses and physiological stress indicators.pdf 9. 1204-Hidden factors and hidden topics：understanding rating dimensions with review text.pdf 10. 1219-Trust-aware recommender systems.pdf 11. 1233-A matrix factorization technique with trust propagation for recommendation in social networks.pdf 12. 1253 - Performance of Recommender Algorithms on Top-N Recommendation Tasks.pdf 13. 1282-SoRec：social recommendation using probabilistic matrix factorization.pdf 14. 1344-Evaluating Recommendation Systems.pdf 15. 1391-Taking the Human Out of the Loop：A Review of Bayesian Optimization.pdf 16. 1395-Content-based Recommender Systems：State of the Art and Trends.pdf 17. 1417-Neural Collaborative Filtering.pdf 18. 1420-Recommender systems with social regularization.pdf 19. 1461-Collaborative topic modeling for recommending scientific articles.pdf 20. 1468-Incorporating contextual information in recommender systems using a multidimensional approach.pdf 21. 1502-Hybrid web recommender systems.pdf 22. 1586-A contextual-bandit approach to personalized news article recommendation.pdf 23. 1672-The Netflix Prize.pdf 24. 1753-Latent semantic models for collaborative filtering.pdf 25. 1794-The MovieLens Datasets：History and Context.pdf 26. 1797-Improving recommendation lists through topic diversification.pdf 27. 1812-Content-boosted collaborative filtering for improved recommendations.pdf 28. 1829-Content-based book recommending using learning for text categorization.pdf 29. 1835-Propagation of trust and distrust.pdf 30. 1867-Eigentaste：A Constant Time Collaborative Filtering Algorithm.pdf 31. 1877-What makes a helpful online review？a study of customer reviews on amazon.com.pdf 32. 1880-Application of Dimensionality Reduction in Recommender System - A Case Study.pdf 33. 1899-The influence of online product recommendations on consumers' online choices.pdf 34. 2037-Collaborative filtering recommender systems.pdf 35. 2056-Methods and metrics for cold-start recommendations.pdf 36. 2362-Recommender systems survey.pdf 37. 2364-Context-Aware Recommender Systems.pdf 38. 2431-E-Commerce Recommendation Applications.pdf 39. 2449-Collaborative Filtering for Implicit Feedback Datasets.pdf 40. 2557-Item-based top- N recommendation algorithms.pdf 41. 2693-A distributed, architecture-centric approach to computing accurate recommendations from very large and sparse datasets.pdf 42. 2779-Content-based recommendation systems.pdf 43. 2897-Collaborative filtering with temporal dynamics.pdf 44. 2980-The dynamics of viral marketing.pdf 45. 3224-Factorization meets the neighborhood：a multifaceted collaborative filtering model.pdf 46. 3618-A Survey of Collaborative Filtering Techniques.pdf 47. 4656-Hybrid Recommender Systems：Survey and Experiments.pdf 48. 6520-Evaluating collaborative filtering recommender systems.pdf 49. 6948-Amazon.com recommendations：item-to-item collaborative filtering.pdf 50. 7459-Matrix Factorization Techniques for Recommender Systems.pdf 51. 9317-Item-based collaborative filtering recommendation algorithms.pdf 52. 11644-Toward the next generation of recommender systems：a survey of the state-of-the-art and possible extensions.pdf

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