DMIN'07 The 2007 International
Conference on Data Mining


Tutorial Sessions








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Conference Chair:
Robert Stahlbock


Conference & Programme
Sven F. Crone
Stefan Lessmann







Tutorial Sessions

Conference tutorials

All tutorials are free to registered conference attendees of all conferences held at WOLDCOMP'07. Those who are interested in attending one or more of the tutorials are to sign up on site at the conference registration desk in Las Vegas.

DMIN'07 Tutorials:

Data Mining in Time Series and Multimedia Databases
Eamonn Keogh
Associate Professor
Computer Science & Engineering Department

University of California - Riverside, USA
Date/Time: Wednesday, June 2
7, 2007 / 6:00pm - 9:00 pm
Ballroom 1

A CD-ROM with tutorial slides, datasets and materials for teaching data mining will be provided in the tutorial session.

Abstract: Time series and multimedia data are ubiquitous; large volumes of such data are routinely created in scientific, industrial, entertainment, medical and biological domains. Examples include gene expression data, electrocardiograms, electroencephalograms, gait analysis, stock market quotes, space telemetry, microarrays, CAT Scans etc. Because such data is intrinsically real valued, most of the work on data mining of text has little utility for such datasets.

A decade ago, a seminal paper by Faloutsos, Ranganathan, Manolopoulos appeared in SIGMOD. The paper, Fast Subsequence Matching in Time-Series Databases, has spawned at least a thousand references and extensions in the database/ data mining and information retrieval communities. This tutorial will summarize the decade of progress in multimedia/time series information retrieval since this influential paper appeared.

Intended audience:  
• Data mining (and Information Retrieval/Database) researchers. Both researchers in general and those working on specific time series/multimedia database problems will find the tutorial informative. The tutorial ends with a discussion of the “top ten” problems to work on in the area, graduate students looking for an interesting problem in a hot area will be well served. 
• Data mining educators (and Information Retrieval/Database). Many professors who teach data mining/information retrieval/databases/machine learning courses use his slides. Such individuals will received his comprehensive (and modifiable) slides and observe his presentation of them. They will be able to base 10 to 20 hours of graduate instruction on the tutorial. 
• Data mining (and Information Retrieval/Database) application developers. They will learn the latest techniques/representations for indexing and mining time series/ multimedia data and examples of how the techniques fit into real-life applications.

Biography of the presenter: Dr. Keoghs research interests are in Data Mining, Machine Learning and Information Retrieval. He has published more than 80 papers in these areas.
Several of his papers have won
“best paper” awards. In addition he has won several teaching awards. He is the recipient of a 5-year NSF Career Award for “Efficient Discovery of Previously Unknown Patterns and Relationships in Massive Time Series Databases” and a grant from Aerospace Corp to develop a time series visualization tool for monitoring space launch telemetry.

Dr Keogh has given well received tutorials on time series, machine learning and data mining all over the world, and his papers have been referenced well over a 2,000 times.

Please see for addition information about his tutorials.

"Awesome tutorial!! It's just wonderful... playful AND deep! I couldn't stop looking at it, even though I've got other things to do....but it was a well spent hour!" (Ben Shneiderman, Founding Director of the Human-Computer Interaction Laboratory, University of Maryland at College Park.)

Introduction to Uncertainty and Fuzzy Logic with Data Mining Applications
Ashu M. G. Solo

Principal/R&D Engineer, Maverick Technologies America Inc.
Wilmington, Delaware, USA

Date/Time: Monday, June 25, 2007 / 5:20pm - 6:00pm
Location: Ballroom 1

For material (slides etc.) please contact Ashu M. G. Solo via email
amgsolo [ a t ] mavericktechnologies [ d o t ] us


Recent technological advances have made it possible to develop computers that are extremely fast and efficient for numerical computations.  However, these computers lack the abilities of humans and animals in processing cognitive information acquired by natural sensors.  For example, the human brain routinely performs tasks like recognizing a face in an unfamiliar crowd in 100-200 ms whereas a computer can take days to accomplish a task of lesser complexity.  The use of fuzzy logic can emulate the desirable computing aspects found in humans and animals.  Engineers and scientists have had many remarkable accomplishments such as putting people on the moon and returning them safely to Earth, sending spacecraft to the far reaches of the solar system, sending rovers to explore the surface of Mars, exploring the oceans depths, designing computers that can perform billions of computations per second, developing the nuclear bomb, mapping the human genome, and constructing a scanning tunneling microscope that can move individual atoms.  But alongside many outstanding achievements using unintelligent systems, there have been many abysmal failures that include modeling the behavior of economic, political, social, physical, and biological systems.  Engineers have been unable to develop technology that can decipher sloppy handwriting, recognize oral speech as well as a human can, translate between languages as well as a human interpreter, drive a car in heavy traffic as well as a human can, walk with the agility of a human or animal, replace the combat infantry soldier, determine the veracity of a statement by a human subject with an acceptable degree of accuracy, replace judges and juries, summarize a complicated document, and explain poetry or song lyrics.  These remaining challenges and many more can benefit from fuzzy logic.

Certainty and precision have much too often become an absolute standard in design, decision making, and control problems.  The excess of precision and certainty in engineering and scientific research and development is often providing unrealizable solutions.  Fuzzy logic, based on the notion of relative graded membership, can deal with information arising from computational perception and cognition that is uncertain, imprecise, vague, partially true, or without sharp boundaries.  Fuzzy logic allows for the inclusion of vague human assessments in computing problems.  Also, it provides an effective means for conflict resolution of multiple criteria and better assessment of options.  New computing methods based on fuzzy logic can lead to greater adaptability, tractability, robustness, and a lower cost solution in the development of intelligent systems for decision making, identification, recognition, optimization, and control. 

Fuzzy logic has been used in numerous applications such as data mining, facial pattern recognition, washing machines, vacuum cleaners, antiskid braking systems, transmission systems, control of subway systems and unmanned helicopters, intelligent communication networks, knowledge-based systems for multiobjective optimization of power systems, weather forecasting systems, models for new product pricing or project risk assessment, medical diagnosis and treatment plans, and stock trading. 

The objective of this tutorial is to provide a clear and rapid introduction to key aspects of fuzzy logic including uncertainty, fuzzy sets, linguistic variables, fuzzy rule bases, computational theory of perceptions, computing with words, and fuzzy math.  This tutorial seeks to introduce fuzzy logic concepts mainly through examples of applications in data mining and linguistic evaluations.

Intended audience: This tutorial is for anybody who wishes to learn the theory and applications of fuzzy logic, and will be extremely useful for many people involved in research and development including computer scientists, engineers (computer, electrical, mechanical, civil, chemical, aerospace, agricultural, biomedical, environmental, geological, industrial, mechatronics), mathematicians, social scientists (economics, management, political science, psychology), natural scientists (biology, chemistry, earth science, physics), business analysts, public policy analysts, jurists, medical researchers, etc.

Biography of the presenter: Ashu M. G. Solo is an electrical and computer engineer, mathematician, writer, and entrepreneur.  His primary research interests are in new branches of math, intelligent systems, public policy, and the application of intelligent systems in control systems, computer architecture, power systems, optimization, pattern recognition, decision making, and public policy.  Solo has about 50 publications in these and other fields.  He co-developed some of the best published methods for maintaining power flow in and multiobjective optimization of radial power distribution system operations.  Solo has served on 52 international program committees for 50 research conferences and 2 research multiconferences.  He is the principal of Maverick Technologies America Inc.  Solo previously served honorably as an infantry officer and platoon commander understudy in the Cdn. Army Reserve.


A complete & current list of WORLDCOMP Tutorials can be found here.



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