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Volume 13, Issue 5
Sept/Oct 1999
Theme: Data Mining

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To Volume 13, Issue 6

Rediscovering What You Do:  A Data Mining and Rule Discovery Approach to Business Forecasting with Adaptive, Genetically-Tuned Fuzzy System Models Earl Cox explores ways to make your models more responsive to change in demographics and the economy.
AI@Work Automated Cardiac Monitoring using Holographic/Quantum Neural Technology, Threatened Fauna Adviser:  Tasmania Forestry, Gallagher Integration Includes User Interface to Rule Definition, CLONTECH Uses TextAnalyst to Process Large Volumes of Scientific Texts, Interesting Rules Describe Data.
Distributed Task Coordination with Truth Maintenance Systems:  AI in Air Liner Design Arkady Epshteyn and Richard H. Stottler cover an AI tool which aids the management and coordination of complex tasks.
Data Mining, Modeling, Simulation and Genetic Algorithms in the Chemical Process Industries Paul Van Buskirk describes applications of modeling across numerous arenas.
Data Mining with Self-Organizing Maps:  Best Practices in Finance, Economics, and Modeling Guido Deboeck uses lessons gleaned froma  variety of applications to describe the best processes including analysis, clustering, visualization, and the use of unsupervised neural networks with competitive learning.
Investigating Jitter Methods:  Measuring What Matters Will Dwinnell illustrates how these jitters won't make you nervous when you buy your next house and other real world examples.

Secret Agent Man - Keeping Secrets in the Age of Multi-Agent Collaboration by Don Barker
Intelligence Files - Oracle "mines" Thinking Machines to Acquire Darwin by David Blanchard
AI and the Net - Wear the Web by Mary Kroening
The Book Zone - Data Preparation for Data Mining and Tracking Kalman Filtering Made Easy by Will Dwinnell
Product Updates ---------------------------> 15 late breaking product announcements from around the world in the fields of:
  Business Rules Data Mining
  Forecasting Intelligent Agents
  Languages Modeling and Simulation
  Neural Networks Announcements
Product Service Guide - Provides access to information on an entire category of products    
PC AI Blackboard - AI advertisers bulletin board    

Advertiser List for 13.5
AAAI  Frontier GlobalCenter  Search Software America 
Amzi! Inc Knowledge Brokers Inc StatSoft 
AI Developers Logic Programming Associates System Dynamics International Inc
Angoss Lumina Decision Systems The Haley Enterprise Inc 
AND Corporation  Megaputer Intelligence Ward Systems Group Inc
Applied Logic Systems Metus Systems WizSoft Inc
ATTAR Software USA  NeuroDimension Inc   
BioComp PC AI   
Blaze Corporation QMC  
BotSpot  Production Systems Technology   
California Scientific Software  Prolog Development Center   
DCI  Salford Systems  
DTSoftware .  Soft Warehouse Inc  
Franz, Inc  Sonalysts Inc   


Data Mining - As Close as Your Grocer

Many of you have or are aware of membership cards provided by larger grocery store chains.  These cards, while providing the holder with modest cost savings, allow the merchant to continuoulsy amass information about their clients' shopping habits.  What these grocers have discovered is that the conventional use of "averages" and "totals" hides valuable information.  As it turns out, their most important customers are not average and don't have average shopping habits.  For example, although a certain wine doesn't rate high in total sales, it may be very popular among the highest spending shoppers.  Even though this particular brand may be lost in the "averages" it brings shoppers into the store.  If the wine isn't available, the clients might move to a competitor's store.  It is knowledge, such as this brand loyalty, that the merchant needs to discover and maintain and this is also where data mining can shine.  With its ability to collect tremendous amounts of information data, the computer also hides important information.  In this issue we look at techniques and tools that help find and identify this special knowledge.
  Will Dwinnell illustrates additional examples of data in "Investigating Jitter Methods:  Measuring What Matters."  Along with these examples, Will demonstrates how to determine which inputs are important as well as measuring the importance of the inputs and their effect on the output.  In his latest article, Earl Cox examines methods for making business models more responsive to fluctuation in demographics and the economy.  Earl uses a number of different technologies, such as fuzzy logic and genetic algorithms in his data mining.
  Based on his research of numerous data mining applications, Guido Deboeck examines the best practices of applying data mining to finance, economics or marketing applications.  He looks at self-organizing maps, clustering, visualization, and neural networks.
  These are just a few of the examples presented in this issue.  We hope you enjoy it.
  Terry Hengl 

Volume 13-------------------> Issue 1 (Jan/Feb 1998)   Volume 15 Index (2001)
  Issue 2 (Mar/Apr 1998)   Volume 14 Index (2000)
Issue 3 (May/Jun 1998)   Volume 13 Index (1999)
Issue 4 (Jul/Aug 1998)   Volume 12 Index (1998)
Issue 5 (Sep/Oct 1998)   Volume 11 Index (1997)
Issue 6 (Nov/Dec 1998)   Volume 10 Index (1996)
      Volume 9 Index (1995)
      Volume 8 Index (1994)

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