Kernel methods have been applied successfully in many data mining tasks. Subspace kernel learning was recently proposed to discover an effective low-dimensional subspace of a kern...
Jianhui Chen, Shuiwang Ji, Betul Ceran, Qi Li, Min...
This paper addresses several key issues in the ArnetMiner system, which aims at extracting and mining academic social networks. Specifically, the system focuses on: 1) Extracting ...
Jie Tang, Jing Zhang, Limin Yao, Juanzi Li, Li Zha...
There is an exploding amount of user-generated content on the Web due to the emergence of "Web 2.0" services, such as Blogger, MySpace, Flickr, and del.icio.us. The part...
Ka Cheung Sia, Junghoo Cho, Yun Chi, Belle L. Tsen...
Researchers in the social and behavioral sciences routinely rely on quasi-experimental designs to discover knowledge from large databases. Quasi-experimental designs (QEDs) exploi...
David D. Jensen, Andrew S. Fast, Brian J. Taylor, ...
Information-theoretic clustering aims to exploit information theoretic measures as the clustering criteria. A common practice on this topic is so-called INFO-K-means, which perfor...