推荐系统-从入门到精通

http://blog.sciencenet.cn/home.php?mod=space&uid=210641&do=blog&id=508634为了方便大家从理论到实践，从入门到精通，循序渐进系统地理解和掌握推荐系统相关知识。特做了个读物清单。大家可以按此表阅读，也欢迎提出意见和指出未标明的经典文献以丰富各学科需求（为避免初学者疲于奔命，每个方向只推荐几篇经典文献）。
1. 中文综述(了解概念-入门篇)
a) 个性化推荐系统的研究进展
b) 个性化推荐系统评价方法综述
2. 英文综述(了解概念-进阶篇)
a) 2004ACMTois-Evaluating collaborative filtering recommender systems
b) 2004ACMTois -Introduction to Recommender Systems - Algorithms and evaluation
c) 2005IEEEtkde Toward the next generation of recommender systems - A survey of the state-of-the-art and possible extensions
3. 动手能力(实践算法-入门篇)
a) 2004ACMtois Item-based top-N recommendation algorithms(协同过滤)
b) 2007PRE Bipartite network projection and personal recommendation(网络结构)
4. 动手能力(实践算法-进阶篇)
a) 2010PNAS-Solving the apparent diversity-accuracy dilemma of recommender systems (物质扩散和热传导)
b) 2009NJP Accurate and diverse recommendations via eliminating redundant correlations (多步物质扩散)
c) 2008EPL Effect of initial configuration on network-based Recommendation (初始资源分配问题)
5. 推荐系统扩展应用(进阶篇)
a) 2009EPJB Predicting missing links via local information(相似性度量方法)
b) 2010theis-Evaluating Collaborative Filtering over time(基于时间效应的博士论文)
c) 2009PA Personalized recommendation via integrated diffusion on user-item-tag tripartite graphs (基于标签的三部分图方法)
d) 2004LNCS Trust-aware collaborative filtering for recommender systems（基于信任机制）
e) 1997CA-Fab_content-based, collaborative recommendation(基于文本信息)
6. 推荐结果的解释(进阶篇)
a) 2000CSCW-Explaining Collaborative Filtering Recommendations
b) 2011PRE-Information filtering via biased heat conduction
c) 2011PRE- Information filtering via preferential diffusion
d) 2010EPL Link Prediction in weighted networks - The role of weak ties
e) 2010EPL-Solving the cold-start problem in recommender systems with social tags
7. 推荐系统综合篇(专著、大型综述、博士论文)
a) 2005Ziegler-thesis-Towards Decentralized Recommender Systems
b) 2010Recommender Systems Handbook