Briefs

This announcement includes KnowledgeMiner 4.0 release,
a Book about KnowledgeMiner, and 2 conference related to GMDH -- inductive
modeling.

KnowledgeMiner is a powerful modeling and prediction tool which
was designed to support the automation of knowledge extraction from data. It
works using three advanced self-organizing modeling technologies:
Statistical learning GMDH Neural Networks, Analog Complexing, and Fuzzy Rule
Induction. This is the first time that all of these algorithms have been
available in one place on any computer platform. Also, as it learns about a
new dataset, it generates equations, patterns, or rules on the fly that
model that data.

KnowledgeMiner can be downloaded from:
http://www.knowledgeminer.net

Version 4.0 features

   - extended AppleScript support (Mac)
      - workflow processing - reading data from databases or spreadsheets,
        data preprocessing, data mining, prediction/classification of new
        data, and returning processed data - by running a single script
      - creating and predicting from within a script
      - creating documents of a certain table dimension via AppleScript
   - calculation of the ROC integral as a measure of classification
     power of a model
   - first version that runs on Windows 98, 2000, and NT using Ardi's
     Executor Mac OS runtime environment (Windows)

With the extended AppleScript support now available in KnowledgeMiner 4.0,
it is possible to control and automate the knowledge discovery process via a
single script. In this way, KnowledgeMiner users can embed advanced data
mining technology into personal solutions, automate repetitive tasks in
simulations, create their own intelligent agents and display real time data
mining on the internet.

KnowledgeMiner empowers businesses and private users with its combination of
ease of use, advanced self-organizing data mining technologies and the
personalization and workflow capabilities of AppleScript. KnowledgeMiner is
the first Personal Data Mining software.

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 Book about Personal Data Mining and KnowledgeMiner
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Many people have wanted to learn more about self-organizing modeling and the
basic ideas behind KM's modeling methods. Prof. J.-A. Mueller and Frank
Lemke have just finished a book called "Self-Organising Data Mining.
Extracting Knowledge From Data."

This book provides a comprehensive view of all major issues related to
self-organizing data mining and its application to solving real-world
problems, and it answers the following questions.

- What makes self-organizing data mining different from other data
  mining methods?
- What problems can be solved by self-organizing data mining in general
  and by using KnowledgeMiner specifically?
- How to prepare a problem for solution as demonstrated using several
  examples from economy, ecology, and sociology.

The book is available now on our website as a Adobe Acrobat PDF. It is
also included in every regular copy of KnowledgeMiner.

For more information on KnowledgeMiner or the book go to our web site:

http://www.knowledgeminer.net

or email info@knowledgeminer.net

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Conference Calls
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In 2002, there are two conferences on inductive (GMDH) modeling:

1. International Conference on Inductive Modeling
May 20-25, 2002
Lviv, Ukraine

The International Conference on
Modeling and Simulating of Complex System
June 11-14, 2002
Sichuan University, Chengdu, P. R. China

More info can be found at

http://www.knowledgeminer.net/news.htm