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2017.5.8-2017.5.12大数据图模型计算Pregel实践

(2017-05-12 20:32:36)
标签:

hadoop

giraph

pregel

分类: 云计算
最近实际项目需要构建复杂网络,这块一直没有实践,之前主要是看看paper,尤其是大数据下的图计算模型。基于hadoop的图计算框架giraph(facebook实践),通过实践对pregel的理解更加深入,实现热传导算法等等。
hadoop graph框架学习和实践   giraph http://giraph.apache.org/ , http://grafos.ml/  http://arabesque.io/
Arabesque: A System for Distributed Graph Mining http://sigops.org/sosp/sosp15/current/2015-Monterey/printable/093-teixeira.pdf
tensorflow https://github.com/skcript/tensorflow-resources
spark https://github.com/endymecy/spark-ml-source-analysis
spark 关闭运行日志 http://stackoverflow.com/questions/25193488/how-to-turn-off-info-logging-in-pyspark
Architecture of Giants: Data Stacks at Facebook, Netflix, Airbnb, and Pinterest https://blog.keen.io/architecture-of-giants-data-stacks-at-facebook-netflix-airbnb-and-pinterest-9b7cd881af54?imm_mid=0f1550
TensorFlow template application for deep learning https://github.com/tobegit3hub/deep_recommend_system
Top 20 Recent Research Papers on Machine Learning and Deep Learning http://www.kdnuggets.com/2017/04/top-20-papers-machine-learning.html
jblas http://jblas.org/
spark 机器学习 https://book.douban.com/subject/26350074/
machine learning dataset http://persoal.citius.usc.es/manuel.fernandez.delgado/papers/jmlr/data.tar.gz
Do we Need Hundreds of Classifiers to Solve Real World Classification Problems? http://jmlr.org/papers/volume15/delgado14a/delgado14a.pdf
CTR predict
Y. W. Chang, C. J. Hsieh, K. W. Chang, M. Ringgaard, and C.-J. Lin, “Training and testing low- degree polynomial data mappings via linear SVM,” Journal of Machine Learning Research, vol. 11, pp. 1471–1490, 2010.
T. Kudo and Y. Matsumoto, “Fast methods for kernel-based text analysis,” in Proceedings of the 41st Annual Meeting of the Association of Computational Linguistics (ACL), 2003
S. Rendle, “Factorization machines,” in Proceedings of IEEE International Conference on Data Mining (ICDM), pp. 995–1000, 2010.
B. Mcmahan, G. Holt, D. Scully , “Ad Click Prediction: a View from the Trenches”
J. Pan, O. Jin, T. Xu, “Practical Lessons from Predicting Clicks on Ads at Facebook”
Y. Juan, Y. Xhuang, W, Chin, “Field-aware Factorization Machines for CTR Prediction”
G. James, D. Witten, T. Hastie, R. Tibshirani, “An Introduction to Statistical Learning”, 2013.
Neural Models for Information Retrieval https://arxiv.org/pdf/1705.01509.pdf
https://kowshik.github.io/JPregel/pregel_paper.pdf Pregel: A System for Large-Scale Graph Processing
Learning Piece-wise Linear Models from Large Scale Data for Ad Click Prediction https://arxiv.org/abs/1704.05194
High Performance Linear Algebra OOP https://github.com/fommil/matrix-toolkits-java
抓取京东评论数据 https://github.com/awolfly9 

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