文件名称：推荐系统的循序进阶读物（从入门到精通）
文件大小：18.11MB
文件格式：RAR
更新时间：2016-02-08 03:45:54
推荐系统 协同过率 卡方
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 （此处分享的是2011年版）
【文件预览】：
推荐系统的循序进阶读物（从入门到精通）
----3a_Item-based top-N recommendation algorithms.pdf(363KB)
----5e_Fab_content-based, collaborative recommendation.pdf(485KB)
----5b_Evaluating Collaborative Filtering over time.pdf(203KB)
----1b_个性化推荐系统评价方法综述.pdf(685KB)
----6e_Solving the cold-start problem in recommender systems with social tags.pdf(438KB)
----概述.txt(2KB)
----7a_Towards Decentralized Recommender Systems.pdf(2MB)
----3b_Bipartite_network_projection_and_personal_recommendation(网络结构).pdf(209KB)
----2a_Evaluating_collaborative_filtering_recommender_systems.pdf(347KB)
----6a_Explaining Collaborative Filtering Recommendations.pdf(365KB)
----5a_Predicting missing links via local information.pdf(191KB)
----5d_Trust-aware Collaborative Filtering for.pdf(154KB)
----7b_Recommender Systems Handbook.pdf(8.33MB)
----4c_Effect of initial configuration on network-based Recommendation.pdf(438KB)
----6b_Information filtering via biased heat conduction.pdf(188KB)
----4a_Solving the apparent diversity-accuracy dilemma of recommender systems.pdf(1.27MB)
----2b_Introduction to Recommender Systems_Algorithms and evaluation.pdf(20KB)
----6d_Link Prediction in weighted networks_The role of weak ties.pdf(321KB)
----2c_Toward_the_Next_Generation_of_Recommender_Systems_A_Survey_of_the_State-of-the-Art_and_Possible_Exte.pdf(557KB)
----5c_Personalized recommendation via integrated diffusion on user-item-tag tripartite graphs.pdf(306KB)
----6c_2011PRE-Information filtering via preferential diffusion.pdf(1.03MB)
----4b_Accurate and diverse recommendations via eliminating redundant correlations.pdf(1.37MB)
----1a_个性化推荐系统的研究进展.pdf(1.37MB)