Knowledge management technologies and applications—literature review from 1995 to 2002
S Liao - Expert systems with applications, 2003 - Elsevier
This paper surveys knowledge management (KM) development using a literature review
and classification of articles from 1995 to 2002 with keyword index in order to explore how …
and classification of articles from 1995 to 2002 with keyword index in order to explore how …
Utility computing and global grids
CS Yeo, MD de Assunção, J Yu, A Sulistio… - arXiv preprint cs …, 2006 - arxiv.org
This chapter focuses on the use of Grid technologies to achieve utility computing. An
overview of how Grids can support utility computing is first presented through the …
overview of how Grids can support utility computing is first presented through the …
Grid-enabling data mining applications with DataMiningGrid: An architectural perspective
V Stankovski, M Swain, V Kravtsov, T Niessen… - Future Generation …, 2008 - Elsevier
The DataMiningGrid system has been designed to meet the requirements of modern and
distributed data mining scenarios. Based on the Globus Toolkit and other open technology …
distributed data mining scenarios. Based on the Globus Toolkit and other open technology …
Global data mining: An empirical study of current trends, future forecasts and technology diffusions
HH Tsai - Expert systems with applications, 2012 - Elsevier
Using a bibliometric approach, this paper analyzes research trends and forecasts of data
mining from 1989 to 2009 by locating heading “data mining” in topic in the SSCI database …
mining from 1989 to 2009 by locating heading “data mining” in topic in the SSCI database …
Parallel TID-based frequent pattern mining algorithm on a PC Cluster and grid computing system
The mining of frequent patterns from transaction-oriented databases is an important subject.
Frequent patterns are fundamental in generating association rules, time series, etc. Most …
Frequent patterns are fundamental in generating association rules, time series, etc. Most …
[PDF][PDF] Towards integrative causal analysis of heterogeneous data sets and studies
We present methods able to predict the presence and strength of conditional and
unconditional dependencies (correlations) between two variables Y and Z never jointly …
unconditional dependencies (correlations) between two variables Y and Z never jointly …
Distributed data mining services leveraging WSRF
The continuous increase of data volumes available from many sources raises new
challenges for their effective understanding. Knowledge discovery in large data repositories …
challenges for their effective understanding. Knowledge discovery in large data repositories …
A fast and resource efficient mining algorithm for discovering frequent patterns in distributed computing environments
KW Lin, SH Chung - Future generation computer systems, 2015 - Elsevier
The advancement of electronic technology enables us to collect logs from various devices.
Such logs require detailed analysis in order to be broadly useful. Data mining is a technique …
Such logs require detailed analysis in order to be broadly useful. Data mining is a technique …
A decision tree algorithm for distributed data mining: Towards network intrusion detection
S Baik, J Bala - … Conference on Computational Science and Its …, 2004 - Springer
This paper presents preliminary works on an agent-based approach for distributed learning
of decision trees. The distributed decision tree approach is applied to intrusion detection …
of decision trees. The distributed decision tree approach is applied to intrusion detection …
Design and implementation of a data mining grid-aware architecture
Current business processes often use data from several sources. Data is characterized to be
heterogeneous, incomplete and usually involves a huge amount of records. This implies that …
heterogeneous, incomplete and usually involves a huge amount of records. This implies that …