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The QUEST Data Mining Group
IBM's 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.
http://www.almaden.ibm.com/software/quest/
Information 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.
http://kind.siit.tu.ac.th/irdm/
Resource Aware Ubiquitous Data Mining Project
Focus on developing a resource-aware ubiquitous data mining system using different algorithmic and optimization techniques.
http://www.csse.monash.edu.au/~mgaber/main.html
SIIT Knowledge Information & Data Management Laboratory
Sirindhorn International Institute of Technology's center of research in knowledge discovery, information engineering, speech and natural language processing.
http://kind.siit.tu.ac.th/
Australian Antarctic Data Mining Resources
Contains information on current research projects involving data mining as well as links and resources.
http://www.antdiv.gov.au/default.asp?casid=5000
Microsoft's Data Mining Research
Details of current data mining research within Microsoft. Includes information on papers and people.
http://research.microsoft.com/dmx/DataMining/
Data Mining and Bioinformatics Research, University of Sunderland
James Malone 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 - the Armada software.
http://www.jamesmalone.plus.com
CRISP-DM
Project 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.
http://www.crisp-dm.org/
DBMiner and Data Mining Projects
Intelligent database systems research laboratory, Simon Fraser University. Includes downloadable research theses and publications.
http://db.cs.sfu.ca/
Data Miners
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.
http://www.cs.Helsinki.FI/research/pmdm/datamining/
Data 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.
http://chem-eng.utoronto.ca/~datamining/index.html
Incremental 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.
http://www.cs.iastate.edu/~honavar/ailab/projects/inclearn.html
Interactive Visual Overviews of Large Multi-Dimensional Datasets
Exploratory data analysis through machine learning and visualization. Work from AIRL, Dept. of CS, Iowa State University.
http://www.cs.iastate.edu/~honavar/ailab/projects/eda.html
Visual Datamining in Material Research
A project on application of visual datamining in material research. The project uses parallel coordinates for multivariate visualization.
http://www.geocities.com/anand_palm
Data Mining Information
Information on KDD applications and systems. Also includes a glossary and success stories.
http://www.lri.fr/iasi/introduction.en.html
Geoff Webb's Research
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.
http://www.cm.deakin.edu.au/webb/
Machine 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.
http://research.microsoft.com/mlas/
Approximate Query Answering (AQUA)
A project for exploratory data analysis. Through Bell Labs.
http://www.bell-labs.com/project/aqua/
Equicom, Inc. Unsupervised Data Clustering
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 of parameters.
http://www.matrixreasoning.com
Center 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.
http://www.insight.nau.edu/
Xelopes Data Mining Library
The 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.
http://www.zsoft.ru
National 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.
http://www.ncdm.uic.edu/
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