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...
A generic and extendible Multi-Agent Data Mining (MADM) framework, EMADS (the Extendible Multi-Agent Data mining System) is described. The central feature of the framework is that ...
Data mining has been defined as the non- trivial extraction of implicit, previously unknown and potentially useful information from data. Association mining is one of the important...
Peter Bollmann-Sdorra, Aladdin Hafez, Vijay V. Rag...
There has been increasing interest in automatic techniques for generating roles for role based access control, a process known as role mining. Most role mining approaches assume t...
Ian Molloy, Ninghui Li, Yuan (Alan) Qi, Jorge Lobo...
Knowledge discovery in databases and data mining aim at semiautomatic tools for the analysis of large data sets. We give an overview of the area and present someof the research is...