mangdun的专栏

谷歌大牛们在SIGGRAPH（Special Interest Group for Computer GRAPHICS，计算机图形图像特别兴趣小组）上的ppt文件

CRF在关系提取方面的应用,但主要是介绍基础的CRF知识,值得认真学习An Introduction to crf for relation learnig.pdf

Andrew McCallum 可以说是Maximum Entropy Markov Models的开山鼻祖,在CRF也贡献颇多,他写的CRF教程值得认真学习. 全英文,An Introduction to Conditional Random Fields

著名的Netflix 智能推荐 百万美金大奖赛使用是数据集. 因为竞赛关闭, Netflix官网上已无法下载. Netflix provided a training data set of 100,480,507 ratings that 480,189 users gave to 17,770 movies. Each training rating is a quadruplet of the form . The user and movie fields are integer IDs, while grades are from 1 to 5 (integral) stars.[3] The qualifying data set contains over 2,817,131 triplets of the form , with grades known only to the jury. A participating team's algorithm must predict grades on the entire qualifying set, but they are only informed of the score for half of the data, the quiz set of 1,408,342 ratings. The other half is the test set of 1,408,789, and performance on this is used by the jury to determine potential prize winners. Only the judges know which ratings are in the quiz set, and which are in the test set—this arrangement is intended to make it difficult to hill climb on the test set. Submitted predictions are scored against the true grades in terms of root mean squared error (RMSE), and the goal is to reduce this error as much as possible. Note that while the actual grades are integers in the range 1 to 5, submitted predictions need not be. Netflix also identified a probe subset of 1,408,395 ratings within the training data set. The probe, quiz, and test data sets were chosen to have similar statistical properties. In summary, the data used in the Netflix Prize looks as follows: Training set (99,072,112 ratings not including the probe set, 100,480,507 including the probe set) Probe set (1,408,395 ratings) Qualifying set (2,817,131 ratings) consisting of: Test set (1,408,789 ratings), used to determine winners Quiz set (1,408,342 ratings), used to calculate leaderboard scores For each movie, title and year of release are provided in a separate dataset. No information at all is provided about users. In order to protect the privacy of customers, "some of the rating data for some customers in the training and qualifyin

Joomla! Development - A Beginner’s Guide 涉及最新的2.5版, 是进行Joomla!开发的难得入门教程

Joomla! 2.5 Beginner's guide ,这是免版权免费发放的入门书,英文pdf格式

ezcomponent是一套低耦合度的php基础工具组件, 大名鼎鼎的ezPublish就是使用这套组件

SimpleGraph是一个完全免费的delphi图形工具,利用它可以方便的在软件中集成图形功能,制作出一流的用户图形交互界面.这是最新的2.7.2版