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 academics for educational and resource purposes. The QUEST team were also responsible for the creation of the paradigm of Association Rules in 1993.
Approximate Query Answering (AQUA)
A project for exploratory data analysis, aiming to improve responses for large database queries. Through Bell Labs.
Australian Antarctic Data Mining Resources
Contains information on current research projects involving data mining as well as links and resources.
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.
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.
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.
Data Mining and Bioinformatics Research, University of Sunderland
James Malone is a PhD Researcher at the University of Sunderland. His research encompasses data mining, machine learning, Bioinformatics and Proteomics. This site also offers a free Association Rule data mining tool - the Armada software.
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.
Data Mining Information
Information on KDD applications and systems. Also includes a glossary and success stories.
DBMiner and Data Mining Projects
Intelligent database systems research laboratory, Simon Fraser University. Includes downloadable research theses and publications.
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.
Geoff Webb's Research
Professor of Computer Science at Monash University. Data mining, machine learning and user modeling research includes k-Optimal Rule Discovery (as exemplified by the Magnum Opus system), OPUS (an efficient search algorithm for exploring the space of conjunctive rules), learning complex conditional probabilities from data (as exemplified by the AODE algorithm), MultiBoosting, decision tree grafting and Feature Based Modeling (the first application of an association-rule-like approach to user modeling).
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.
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.
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.
Microsoft Data Mining Research
A long term Knowledge Discovery and Data Mining project which has the current short-term goals of research into (i) the integration of data mining with database systems and (ii) scalable data mining algorithms.
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.
Resource Aware Ubiquitous Data Mining Project
Focus on developing a resource-aware ubiquitous data mining system using different algorithmic and optimization techniques.
University of Helsinki data mining and machine learning project
This website details project developments into methods and tools for analyzing large data sets and for searching for unexpected relationships in the data. The project combines development of combinatorial pattern matching algorithms with statistical techniques and database methods. The project has also studied the construction of efficient predictors from large masses of data.
Visual Datamining in Material Research
A project on application of visual datamining in material research. The project uses parallel coordinates for multivariate visualization.
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