分享一些关于推荐的书籍、论文和资料

[pspcxl]

小弟是一个新人，初来乍到，没有什么可以贡献的，先贴出来一些自己在各个地方收集的一些关于推荐系统的资料，如下：（同时有什么缺漏希望大家可以补充一下，其中不少是参照组里给的一些信息。）
书籍：
Programming Collective Intelligence - OReilly - Aug 2007.pdf
recommender systems handbook
论文：
1、综述
刘建国，周涛，汪秉宏. 个性化推荐系统的研究进展[J]. 自然科学进展. 2009, 19(001): 1-15.[1]
刘建国，周涛，郭强，等. 个性化推荐系统评价方法综述[J]. 复杂系统与复杂性科学. 2009, 6(003): 1-10.[2]
Toward the next generation of recommender systems - A survey of the state-of-the-art and possible extensions[3]
2、Content-Based
Fab: content-based collaborative recommendation[4]
3、KNN：
GroupLens: an open architecture for collaborative filtering of netnews[5]
Amazon. com recommendations: Item-to-item collaborative filtering[6]
Item-based top-n recommendation algorithms[7]
4、SVD相关系列
Matrix factorization techniques for recommender systems[8]
Factorization meets the neighborhood: a multifaceted collaborative filtering model[9]
5、图算法
Bipartite network projection and personal recommendation[10]
6、slope-one：
Slope one predictors for online rating-based collaborative filtering[11]
7、冷启动：
Methods and Metrics for Cold-Start Recommendations[12]
Adaptive bootstrapping of recommender systems using decision trees[13]
8、博士论文
Learning to Recommend[14]
Netflixprize中的协作过滤算法[15]
动态推荐系统关键技术研究[16]
9.其它
Resnick P, Iacovou N, Suchak M, et al. GroupLens: an open architecture for collaborative filtering of netnews[C]. ACM, 1994.[17]
Golbandi N, Koren Y, Lempel R. Adaptive bootstrapping of recommender systems using decision trees[C]. Hong Kong, China: ACM,2011.[18]
Ma H. Learning to Recommend[D]. 2009.[19]
吴金龙. Netflixprize中的协作过滤算法[D]. 2009.[20]
项亮. 动态推荐系统关键技术研究[D]. 2011.[21]
博客：
http://blog.sciencenet.cn/home.php?mod=space&uid=210641&do=blog&id=508634
http://www.ibm.com/developerworks/cn/web/1103_zhaoct_recommstudy1/index.html?ca=drs-
http://www.ibm.com/developerworks/cn/web/1103_zhaoct_recommstudy2/index.html?ca=drs-
http://www.ibm.com/developerworks/cn/web/1103_zhaoct_recommstudy3/index.html?ca=drs-

[xudong zhao]

求大家再补充一些与推荐系统评价方法相关的资料。3Q~

[史艳翠]

你好，我想看看 “动态推荐系统关键技术研究”这篇论文，你那有吗？我在网上找了一下，没有找到。如果你那有可以发到我邮箱吗？

[chao yin]

http://www.slideshare.net/xlvector/phd-thesis-temporal-recommendation
这里有ppt

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Best regards,
英超

[史艳翠]

多谢

[Wang Jun]

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Programming Collective Intelligence - OReilly - Aug 2007.pdf
recommender systems handbook

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Toward the next generation of recommender systems - A survey of the state-of-the-art and possible extensions[3]
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Fab: content-based collaborative recommendation[4]
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GroupLens: an open architecture for collaborative filtering of netnews[5]
Amazon. com recommendations: Item-to-item collaborative filtering[6]
Item-based top-n recommendation algorithms[7]

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Matrix factorization techniques for recommender systems[8]
Factorization meets the neighborhood: a multifaceted collaborative filtering model[9]

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Bipartite network projection and personal recommendation[10]
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Slope one predictors for online rating-based collaborative filtering[11]

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Methods and Metrics for Cold-Start Recommendations[12]
Adaptive bootstrapping of recommender systems using decision trees[13]

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Learning to Recommend[14]
Netflixprize�е�Э�������㷨[15]
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Resnick P, Iacovou N, Suchak M, et al. GroupLens: an open architecture for collaborative filtering of netnews[C]. ACM, 1994.[17]
Golbandi N, Koren Y, Lempel R. Adaptive bootstrapping of recommender systems using decision trees[C]. Hong Kong, China: ACM,2011.[18]
Ma H. Learning to Recommend[D]. 2009.[19]

�����. Netflixprize�е�Э�������㷨[D]. 2009.[20]
����. ��̬�Ƽ�ϵͳ�ؼ����о�[D]. 2011.[21]
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http://blog.sciencenet.cn/home.php?mod=space&uid=210641&do=blog&id=508634
http://www.ibm.com/developerworks/cn/web/1103_zhaoct_recommstudy1/index.html?ca=drs-
http://www.ibm.com/developerworks/cn/web/1103_zhaoct_recommstudy2/index.html?ca=drs-
http://www.ibm.com/developerworks/cn/web/1103_zhaoct_recommstudy3/index.html?ca=drs-

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--
Best regards,
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