会议

数据挖掘

##QQ群

机器学习&模式识别 246159753
数据挖掘机器学习 236347059
推荐系统 274750470

##Github

###推荐系统

推荐系统开源软件列表汇总和评点 http://in.sdo.com/?p=1707
Mrec(Python) https://github.com/mendeley/mrec
Crab(Python) https://github.com/muricoca/crab
Python-recsys(Python) https://github.com/ocelma/python-recsys
CofiRank(C++) https://github.com/markusweimer/cofirank
GraphLab(C++) https://github.com/graphlab-code/graphlab
EasyRec(Java) https://github.com/hernad/easyrec
Lenskit(Java) https://github.com/grouplens/lenskit
Mahout(Java) https://github.com/apache/mahout
Recommendable(Ruby) https://github.com/davidcelis/recommendable

###库

NLTK https://github.com/nltk/nltk
Pattern https://github.com/clips/pattern
Pyrallel https://github.com/pydata/pyrallel
Theano https://github.com/Theano/Theano
Pylearn2 https://github.com/lisa-lab/pylearn2
TextBlob https://github.com/sloria/TextBlob
MBSP https://github.com/clips/MBSP
Gensim https://github.com/piskvorky/gensim
Langid.py https://github.com/saffsd/langid.py
Jieba https://github.com/fxsjy/jieba
xTAS https://github.com/NLeSC/xtas
NumPy https://github.com/numpy/numpy
SciPy https://github.com/scipy/scipy
Matplotlib https://github.com/matplotlib/matplotlib
scikit-learn https://github.com/scikit-learn/scikit-learn
Pandas https://github.com/pydata/pandas
MDP http://mdp-toolkit.sourceforge.net/
PyBrain https://github.com/pybrain/pybrain
PyML http://pyml.sourceforge.net/
Milk https://github.com/luispedro/milk
PyMVPA https://github.com/PyMVPA/PyMVPA
TensorFlow https://github.com/tensorflow/tensorflow

博客

周涛 http://blog.sciencenet.cn/home.php?mod=space&uid=3075
Greg Linden http://glinden.blogspot.com/
Marcel Caraciolo http://aimotion.blogspot.com/
RsysChina http://weibo.com/p/1005051686952981
推荐系统人人小站 http://zhan.renren.com/recommendersystem
阿稳 http://www.wentrue.net
梁斌 http://weibo.com/pennyliang
刁瑞 http://diaorui.net
guwendong http://www.guwendong.com
xlvector http://xlvector.net
懒惰啊我 http://www.cnblogs.com/flclain/
free mind http://blog.pluskid.org/
lovebingkuai http://lovebingkuai.diandian.com/
LeftNotEasy http://www.cnblogs.com/LeftNotEasy
LSRS 2013 http://graphlab.org/lsrs2013/program/
Google小组 https://groups.google.com/forum/#!forum/resys
Journal of Machine Learning Research http://jmlr.org/
在线的机器学习社区 http://www.52ml.net/16336.html
清华大学信息检索组 http://www.thuir.cn
我爱自然语言处理 http://www.52nlp.cn/
数据挖掘与数据分析http://spss-market.r.blog.163.com/

##文章

心中永远的正能量 http://blog.csdn.net/yunlong34574
机器学习最佳入门学习资料汇总 http://article.yeeyan.org/view/22139/410514
Books for Machine Learning with R http://www.52ml.net/16312.html
是什么阻碍了你的机器学习目标？ http://www.52ml.net/16436.htm
推荐系统初探 http://yongfeng.me/attach/rs-survey-zhang-slices.pdf
推荐系统中协同过滤算法若干问题的研究 http://pan.baidu.com/s/1bnjDBYZ
Netflix 推荐系统：第一部分 http://blog.csdn.net/bornhe/article/details/8222450
Netflix 推荐系统：第二部分 http://blog.csdn.net/bornhe/article/details/8222497
探索推荐引擎内部的秘密 http://www.ibm.com/developerworks/cn/web/1103_zhaoct_recommstudy1/index.html
推荐系统resys小组线下活动见闻2009-08-22 http://www.tuicool.com/articles/vUvQVn
Recommendation Engines Seminar Paper, Thomas Hess, 2009: 推荐引擎的总结性文章 http://www.slideshare.net/antiraum/recommender-engines-seminar-paper
Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions, Adomavicius, G.; Tuzhilin, A., 2005 http://dl.acm.org/citation.cfm?id=1070751
A Taxonomy of RecommenderAgents on the Internet, Montaner, M.; Lopez, B.; de la Rosa, J. L., 2003 http://www.springerlink.com/index/KK844421T5466K35.pdf
A Course in Machine Learning http://ciml.info/
基于mahout构建社会化推荐引擎 http://www.doc88.com/p-745821989892.html
个性化推荐技术漫谈 http://blog.csdn.net/java060515/archive/2007/04/19/1570243.aspx
Design of Recommender System http://www.slideshare.net/rashmi/design-of-recommender-systems
How to build a recommender system http://www.slideshare.net/blueace/how-to-build-a-recommender-system-presentation
推荐系统架构小结 http://blog.csdn.net/idonot/article/details/7996733
System Architectures for Personalization and Recommendation http://techblog.netflix.com/2013/03/system-architectures-for.html
The Netflix Tech Blog http://techblog.netflix.com/
百分点推荐引擎——从需求到架构http://www.infoq.com/cn/articles/baifendian-recommendation-engine
推荐系统在InfoQ上的内容 http://www.infoq.com/cn/recommend
推荐系统实时化的实践和思考 http://www.infoq.com/cn/presentations/recommended-system-real-time-practice-thinking
质量保证的推荐实践 http://www.infoq.com/cn/news/2013/10/testing-practice/
推荐系统的工程挑战 http://www.infoq.com/cn/presentations/Recommend-system-engineering
社会化推荐在人人网的应用 http://www.infoq.com/cn/articles/zyy-social-recommendation-in-renren/
利用20%时间开发推荐引擎 http://www.infoq.com/cn/presentations/twenty-percent-time-to-develop-recommendation-engine
使用Hadoop和 Mahout实现推荐引擎 http://www.jdon.com/44747
SVD 简介 http://www.cnblogs.com/FengYan/archive/2012/05/06/2480664.html
Netflix推荐系统：从评分预测到消费者法则 http://blog.csdn.net/lzt1983/article/details/7696578
关于数据挖掘学习的讨论https://www.zhihu.com/question/20751219

论文

《推荐系统实战》引用

<a href="http://blog.sciencenet.cn/home.php?mod=attachment&amp;filename=%E3%80%90ACM%20RecSys%202009%20Workshop%E3%80%91Improving%20recommendation%20accuracy%20by%20clustering%20so.pdf&amp;id=37991"
target="_blank">
    
</a>

<a href="http://blog.sciencenet.cn/home.php?mod=attachment&amp;filename=%E3%80%90CIKM%202012%20Best%20Stu%20Paper%E3%80%91Incorporating%20Occupancy%20into%20Frequent%20Pattern%20Mini.pdf&amp;id=37992"
target="_blank">
    【CIKM 2012 Best Stu Paper】Incorporating Occupancy into Frequent Pattern
    Mini.pdf
</a>

<a href="http://blog.sciencenet.cn/home.php?mod=attachment&amp;filename=%E3%80%90CIKM%202012%20poster%E3%80%91A%20Latent%20Pairwise%20Preference%20Learning%20Approach%20for%20Recomme.pdf&amp;id=37993"
target="_blank">
    【CIKM 2012 poster】A Latent Pairwise Preference Learning Approach for Recomme.pdf
</a>

<a href="http://blog.sciencenet.cn/home.php?mod=attachment&amp;filename=%E3%80%90CIKM%202012%20poster%E3%80%91An%20Effective%20Category%20Classification%20Method%20Based%20on%20a%20Lan.pdf&amp;id=37994"
target="_blank">
    【CIKM 2012 poster】An Effective Category Classification Method Based on
    a Lan.pdf
</a>

【CIKM 2012 poster】Learning to Rank for Hybrid Recommendation.pdf

<a href="http://blog.sciencenet.cn/home.php?mod=attachment&amp;filename=%E3%80%90CIKM%202012%20poster%E3%80%91Learning%20to%20Recommend%20with%20Social%20Relation%20Ensemble.pdf&amp;id=37996"
target="_blank">
    【CIKM 2012 poster】Learning to Recommend with Social Relation Ensemble.pdf
</a>

【CIKM 2012 poster】Maximizing Revenue from Strategic Recommendations under De.pdf

【CIKM 2012 poster】On Using Category Experts for Improving the Performance an.pdf

【CIKM 2012 poster】Relation Regularized Subspace Recommending for Related Sci.pdf

【CIKM 2012 poster】Top-N Recommendation through Belief Propagation.pdf

【CIKM 2012 poster】Twitter Hyperlink Recommendation with User-Tweet-Hyperlink.pdf

【CIKM 2012 short】Automatic Query Expansion Based on Tag Recommendation.pdf

【CIKM 2012 short】Graph-Based Workflow Recommendation- On Improving Business .pdf

【CIKM 2012 short】Location-Sensitive Resources Recommendation in Social Taggi.pdf

【CIKM 2012 short】More Than Relevance- High Utility Query Recommendation By M.pdf

【CIKM 2012 short】PathRank- A Novel Node Ranking Measure on a Heterogeneous G.pdf

【CIKM 2012 short】PRemiSE- Personalized News Recommendation via Implicit Soci.pdf

【CIKM 2012 short】Query Recommendation for Children.pdf