|Projects and Research
QUEST Data Mining Group
QUEST team work on several data mining projects, especially techniques for extracting
associations, classifications, sequential patterns and time sequences. They also
provide a free software tool, DB2 Universal Database and Intelligent Miner, to
academic's for educational and resource purposes. The QUEST team were also responsible
for the creation of the paradigm of Association Rules in 1993.
Query Answering (AQUA)
A project for exploratory data analysis. Through
Network Toolkit (BNT)
Windows software and source for construction and
reasoning with Bayesian networks from file or dataset. Includes thesis accompanying
for Data Insight
Comprehensive Data Mining facility where all the elements
of the Data Mining process coexist in one center of excellence. The Center is
partnered with the latest vendors of Data Mining products covering the entire
spectrum of the Data Mining process.
developing an industry neutral and tool neutral Data Mining process model. Starting
from the embryonic knowledge discovery processes used in industry today and responding
directly to user requirements.
Data mining or knowledge discovery in databases, is a new research
area developing methods and systems for extracting interesting and useful information
from large sets of data. University of Helsinki.
Mining and Bioinformatics Research, University of Sunderland
is a PhD Researcher at the University of Sunderland. His research encompasses
data mining, AI, Bioinformatics and Proteomics. This site also offers a free Association
Rule data mining tool.
Mining in Engineering
Group combining modern statistical methods, machine
learning, and knowledge of specific application areas to develop new approaches
to data mining. University of Toronto.
Information on KDD applications and systems. Also includes
a glossary and success stories.
and Data Mining Projects
Intelligent database systems research laboratory,
Simon Fraser University. Includes downloadable research theses and publications.
- Equicom, Inc. Unsupervised
Non-biological intelligence concept based on a matrix reasoning
algorithm representing an intelligent data understanding system. The NBI-algorithm
allows for unsupervised hierarchical multi-dimensional clustering based on hundreds
Professor of computing at Deakin University, Burwood, Vic,
Australia. Research includes OPUS (efficient search algorithm for exploring the
space of conjunctive rules), Impact Rules (provide analysis similar to association
rules except that the target is a distribution on a numeric value), Lazy Bayesian
Rules, MultiBoosting, Decision tree grafting.
Learning from Distributed Dynamic Data Sources
Algorithmic and systems
solutions for knowledge acquisition from distributed data sets. Work from AIRL,
Dept. of CS, Iowa State University.
Retrieval and Data Mining (IRDM), SIIT
Information Retrieval and Data Mining
research and development of resources for processing very large scaled information
on the internet. A research group of Knowledge Information & Data Management
(KIND) Lab, Sirindhorn International Institute of Technology, Thailand.
Visual Overviews of Large Multi-Dimensional Datasets
Exploratory data analysis
through machine learning and visualization. Work from AIRL, Dept. of CS, Iowa
Learning and Applied Statistics (MLAS)
Group at Microsoft focused on learning
from data and data mining. By building software that automatically learns from
data, enable applications that do intelligent tasks such as handwriting recognition,
and help human data analysts explore their data.
Center for Data Mining (NCDM)
National Center for Data Mining - A national
resource for high performance and distributed for data mining. The center also
researches several cutting-edge data mining projects.
Aware Ubiquitous Data Mining Project
Focus on developing a resource-aware
ubiquitous data mining system using different algorithmic and optimization techniques.
- Visual Datamining
in Material Research
A project on application of visual datamining in
material research. The project uses parallel coordinates for multivariate visualization.
- Xelopes Data Mining Library
XELOPES library is an open platform-independent and data-source-independent library
for Embedded Data Mining. XELOPES is CWM-compatible, supports the relevant Data
Mining standards and can be combined with all analytical software.