Classical data mining algorithms implicitly assume complete access to all data, either in centralized or federated form. However, privacy and security concerns often prevent sharin...
Privacy and security concerns can prevent sharing of data, derailing data mining projects. Distributed knowledge discovery, if done correctly, can alleviate this problem. The key ...
Traditional methods for data mining typically make the assumption that data is centralized and static. This assumption is no longer tenable. Such methods waste computational and I/...
Adriano Veloso, Matthew Eric Otey, Srinivasan Part...
Huge amounts of data are stored in autonomous, geographically distributed sources. The discovery of previously unknown, implicit and valuable knowledge is a key aspect of the expl...
The prevalent use of social media produces mountains of unlabeled, high-dimensional data. Feature selection has been shown effective in dealing with high-dimensional data for eï¬...