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...
In this paper, we describe disparity, a tool that does parallel, scalable anomaly detection for clusters. Disparity uses basic statistical methods and scalable reduction operation...
We present a scalable parallel implementation for converting a Bayesian network to a junction tree, which can then be used for a complete parallel implementation for exact inferen...
The GridBASE framework for database-driven grid computing is presented. The design and a prototype implementation of the framework is discussed. Industry-strength database technol...
Abstract. We describe a scalable parallel implementation of the self organizing map (SOM) suitable for datamining applications involving clustering or segmentation against large da...
Richard D. Lawrence, George S. Almasi, Holly E. Ru...