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HIPC
2003
Springer
15 years 12 months ago
Parallel and Distributed Frequent Itemset Mining on Dynamic Datasets
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...
HAIS
2009
Springer
15 years 11 months ago
A Generic and Extendible Multi-Agent Data Mining Framework
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 ...
Kamal Ali Albashiri, Frans Coenen
DAWAK
2001
Springer
15 years 11 months ago
A Theoretical Framework for Association Mining Based on the Boolean Retrieval Model
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...
SACMAT
2010
ACM
15 years 11 months ago
Mining roles with noisy data
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...
SSDBM
1996
IEEE
168views Database» more  SSDBM 1996»
15 years 11 months ago
Data Mining: Machine Learning, Statistics, and Databases
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...
Heikki Mannila