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   Home / Computers / Software / Databases / Data Mining
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   See Also
   Web Sites
  • About.com on Data Mining - About.com presents a collection of original feature articles, net links, forum discussions and a chat room dedicated to data mining and data warehousing topics.
    databases.about.com/compute/databases/cs/datamining
  • Bank Of Montreal Mines Knowledge From Data - Jan Mrazek says privacy and performance are key issues in business intelligence and data mining for the Bank of Montreal.
    www.techweb.com/wire/story/TWB19990920S0008
  • CRISP-DM - The CRISP-DM project has developed an industry- and tool-neutral Data Mining process model. The current process model for data mining provides an overview of the life cycle of a data mining project.
    www.crisp-dm.org
  • Data Mining and Knowledge Discovery journal - Data Mining and Knowledge Discovery is a peer reviewed journal publishing articles on all aspects of Knowledge Discovery in Databases (KDD) and data mining methods for extracting high-level representations (patterns and models) from data. Submissions of high-quality original research or technical survey articles of related fields and techniques are welcome. We also publish application papers as well as short (2-page) application summary articles.
    www.digimine.com/usama/datamine
  • Data Mining News - Bi-weekly subscription newsletter devoted to covering KDD industry, published by the Bethesda, Maryland-based Intelligent Data Analysis Group.
    www.idagroup.com
  • Data Mining on the Web - Article by Dan Greening on data mining techniques applied to analyzing and making decisions from web data.
    www.webtechniques.com/archives/2000/01/greening
  • Data Mining Resources - A collection of Data Mining links edited by the Central Connecticut State University
    www.ccsu.edu/datamining/resources.html
  • Digging Up $$$ with Data Mining - An Executive's Guide - Tim Graettinger. Data mining creates information assets that an organization can leverage to achieve these strategic objectives. In this article, we address some of the key questions executives have about data mining.
    www.tdan.com/i010ht01.htm
  • Distribution Analysis module for PostgreSQL - Graphical parameter distribution and function relations analysis software for PostgreSQL
    web.tiscali.it/wiseminosse/danalysis.html
  • DSS Lab - Includes articles and guides from some of the top applied data miners including Erik Thomsen, George Spofford, and Michael Berry
    www.dsslab.com
  • E-Mining Myth & Magic: Using Data Mining Successfully - by Michael Meltzer
    www.crm-forum.com/library/art/art-048/brandframe.html
  • Estimating Campaign Benefits and Modeling Lift (Overheads) - In assessing the potential of data mining based marketing campaigns one needs to estimate the payoff of applying modeling to the problem of predicting behavior of some target population. We present a methodology for initial cost/benefit analysis and present surprising empirical results, based on actual business data from several domains, on achievable model accuracy.
    www.kdnuggets.com/gpspubs/kdd99-est-ben-lift/index.htm
  • Intelligent Enterprise magazine - Many articles focusing on the use of Data Mining in large enterprises
    www.intelligententerprise.com
  • Joel Ratsaby Research Web Site - Personal Web page describing personal, professional and research capabilities on Intelligent Systems, Data Mining, Bayesian Networks and Learning Theory.
    www.geocities.com/jratsaby/Research.htm
  • Kurt Thearling: Data Mining and CRM - Information on data mining and CRM technology. Includes many articles and white papers
    www3.primushost.com/~kht/index.htm
  • Market Mining Tools - A variety of modeling technologies to create response, retention, and valuation models and marketing analyses. These include Statistical Networks, Linear Regression, Logistic Regression, K-Nearest Neighbor and C4.5 Decision Trees.
    www.marketminer.com
  • Neural Network software for Windows - Two data processing tools for databases based on Neural Network technology to make predictions, to discover patterns and helping on business decisions.
    attrasoft.com
  • OpenITx: Data Mining Discussion Group - The purpose of the Data Mining Discussion Group is to provide IT executives, managers, and professionals with a forum for discussing the appropriate selection of data mining solutions to match their needs.
    www.openitx.com/g/OpenITx/DATAMINING-SELECT.asp
  • Recursive-Partitioning.com -- Supervised & Unsupervised Learning - Recursive partitioning based supervised and unsupervised learning methods resources. Comprehensive lists of classification trees, regression trees, rules induction, and clustering software packages. Extensive bibliography collection. Links to machine learning and data mining websites.
    www.recursive-partitioning.com
  • Shih Data Miner - Modelling tool that analyzes data patterns generating classification, regression or prediction models. Displays data in a graphical friendly way and with a very fast performance.
    213.119.99.174:8080/presentation.html
  • The Data Mine - Launched in April 1994 to provide information about Data Mining (AKA Knowledge Discovery In Databases or KDD). A Twiki site full of guides, info, and links
    www.the-data-mine.com
  • Top Ten Data Mining Questions - Fundamental questions can quickly clarify the business benefits and the power of a data mining system, setting its advantages in a clear perspective.
    www.datamining.com/top10.htm
  • Tyson Software - Flagship product, The Query Tool, a data mining application that performs data analysis upon any SQL database. Data can be sorted, filtered, printed and exported to a variety of formats.
    www.TysonSoftware.co.uk
  • Web-Datamining - Web-datamining.net gather information and exchanges on Data Mining, Statistics and Knowledge Discovery, including publications, meetings and tools. In French and English
    www.web-datamining.net
  • Weka 3 - Data Mining with Open Source Machine Learning Software in Java - Weka is a collection of machine learning algorithms for solving real-world data mining problems. It is written in Java and runs on almost any platform. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka is also well-suited for developing new machine learning schemes. Weka is open source software issued under the GNU General Public License.
    www.cs.waikato.ac.nz/ml/weka

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