Knowledge Discovery Nuggets 97:15, e-mailed 97-05-04
KDD Nuggets Index
To KD Mine: main site for Data Mining and Knowledge Discovery.
To subscribe to KDD Nuggets, email to kdd-request
Past Issues: 97 Nuggets,
1996 Nuggets,
1995 Nuggets,
1994 Nuggets,
1993 Nuggets
Knowledge Discovery Nuggets 97:15, e-mailed 97-05-04
News:
*
R. Uthurusamy, KDD-97 Overview and Tutorials
http://www-aig.jpl.nasa.gov/kdd97-docs/kdd97.tutorials.html
*
R. Uthurusamy, KDD-97 Workshop, Integration of Data Mining and
Data Visualization
http://www.cs.uml.edu/~grinstei/kddvis-workshop.html
*
R. Uthurusamy, KDD-97 Registration Information
http://www-aig.jpl.nasa.gov/kdd97-docs/registrationinfo.html
*
Peter Turney, data mining from wafers manufacturing process
Siftware:
*
Nicolas Bissantz, Delta Miner 3.0
http://www.bissantz.de
Positions:
*
Pablo Tamayo, Job Position at Thinking Machines
Meetings:
*
E. Horvitz, Call for participation, UAI-97,
http://cuai97.microsoft.com
*
Gordian Institute, 'Making Sense of Data: Computer-Aided
Pattern Discovery', July 14-18, Charlottesville, Virginiahttp://www.gordianknot.com
*
R. Zicari, COMDEX Internet & OBJECT WORLD Frankfurt`97 (Oct 7-10)
http://www.ltt.de
--
Data Mining and Knowledge Discovery community, focusing on the
latest research and applications.
Submissions are most welcome and should be emailed, with a
DESCRIPTIVE subject line (and a URL) to gps.
Please keep CFP and meetings announcements short and provide
a URL for details.
To subscribe, seehttp://www.kdnuggets.com/subscribe.html
KD Nuggets frequency is 3-4 times a month.
Back issues of KD Nuggets, a catalog of data mining tools
('Siftware'), pointers to Data Mining Companies, Relevant Websites,
Meetings, and more is available at Knowledge Discovery Mine site
athttp://www.kdnuggets.com/
-- Gregory Piatetsky-Shapiro (editor)
gps
********************* Official disclaimer ***************************
All opinions expressed herein are those of the contributors and not
necessarily of their respective employers (or of KD Nuggets)
*********************************************************************
~~~~~~~~~~~~ Quotable Quote ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
A gentleman is not a pot
Confucius
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Date: Thu, 24 Apr 1997 18:06:38 -0400
From: samy@iss.gm.com
(R. Uthurusamy)
Subject: KDD-97 Registration Information
KDD-97 Registration Brochure
Third International Conference on Knowledge Discovery and Data Mining (KDD-97)
August 14-17, 1997
Sponsored by the American Association for Artificial Intelligence
http://www.aaai.org
KDD-97: A Preview
The rapid growth of data and information has created a need and an
opportunity for extracting knowledge from databases, and both researchers
and application developers have been responding to that need. Knowledge
discovery in databases (KDD), also referred to as data mining, is an area
of common interest to researchers in machine discovery, statistics,
databases, knowledge acquisition, machine learning, data visualization,
high performance computing, and knowledge-based systems. KDD applications
have been developed for astronomy, biology, finance, insurance, marketing,
medicine, and many other fields.
The Third International Conference on Knowledge Discovery and Data Mining
(KDD-97) will follow up the success of KDD-95 and KDD-96 by bringing
together researchers and application developers from different areas
focusing on unifying themes.
KDD-97 Organization
General Conference Chair:
Ramasamy Uthurusamy, General Motors Corporation, USA
Program Cochairs:
David Heckerman, Microsoft Research, USA
Heikki Mannila, University of Helsinki, Finland
Daryl Pregibon, AT&T Laboratories, USA
Publicity Chair:
Paul Stolorz, Jet Propulsion laboratory, USA
Tutorial Chair:
Padhraic Smyth, University of California, Irvine, USA
Demo and Poster Sessions Chair:
Tej Anand, NCR Corporation, USA
Awards Chair:
Gregory Piatetsky-Shapiro, Geneve Consulting, USA
Keynote Speaker:
Peter Huber, Universitat Bayreuth, Germany
'From Large to Huge. A Statistician's Reactions to KDD & DM'
The statistics and AI communities are confronted by the same challenge, the
onslaught of ever larger data collections, but the two communities have
reacted independently and differently. What could they learn from each
other if they looked over the fence? What is amiss on either side?
KDD-97 Tutorial Abstracts and Speakers
--------------------------------------
Full info on tutorials available at
http://www-aig.jpl.nasa.gov/kdd97-docs/kdd97.tutorials.html
All tutorials will be presented on Thursday, August 14, 1997. The times
listed below are tentative. Admission to the tutorials is included in your
conference registration fee. Registrants can attend up to four consecutive
tutorials, including four tutorial syllabi.
8:00 to 10:00am T1- Fayyad and Simoudis (single session)
Session 1 Session 2
10:30am to 12:30pm T2 - Hand T3 - Feldman
1:30 to 3:30pm T4 - Swayne and Cook T5 - Chaudhuri and Dayal
4:00 to 6:00 pm T6 - Keim T7 - DuMouchel
Tutorial 1: 8:00-10:00am
Data Mining and KDD: An Overview
Usama Fayyad, Microsoft Research and Evangelos Simoudis, IBM
We present a basic tutorial of this new and emerging area and emphasize
relations to constituent communities, including statistics, databases,
pattern recognition, learning, and visualization. The tutorial provides a
basic overview of the KDD process for extracting knowledge from databases
and covers the basics of each step in the process including: data
warehousing, selection and cleaning, data transformation, data mining,
evaluation, and visualization. We also cover a sampling of successful
applications and outline challenges and issues to be addressed.
Dr. Usama Fayyad is a Senior Researcher at Microsoft Research, the Decision
Theory & Adaptive Systems Group. His research interests include knowledge
discovery in large databases, data mining, machine learning, statistical
pattern recognition, and clustering. After receiving the Ph.D. degree in
1991, he joined the Jet Propulsion Laboratory (JPL), California Institute
of Technology (until 1996). At JPL, he headed the Machine Learning Systems
Group where he developed data mining systems for analysis of large
scientific databases.
Dr. Evangelos Simoudis is Vice President, Global Business Intelligence
Solutions - IBM North America, where he is responsible for the development
and deployment of data mining and decision support solutions to IBM's
customers worldwide. Dr. Simoudis received a B.A. in Physics from Grinnell
College, a B.S. in Electrical Engineering from California Institute of
Technology, an M.S. in Computer Science from the University of Oregon, and
a Ph.D. in Computer Science from Brandeis University.
Tutorial 2: 10:30am-12:30pm
Modelling Data and Discovering Knowledge
David Hand, Open University, UK
Our aim is to extract knowledge from large bodies of data. The size of
these bodies mean that we cannot do it unaided, but must use fast
computers, applying sophisticated statistical tools. Attempts to automate
the process of knowledge extraction date from at least the early 1980s,
with the work on statistical expert systems. We examine this work, noting
its successes and failures and, especially, what researchers in data mining
and knowledge discover can learn from those efforts. We examine what data
are, what information is, and what knowledge is. We contrast modelling with
discovery, especially in the context of large data sets. We examine high
level modelling issues, such as overfitting, generalisability,
overmodelling, and model evaluation. And we examine high level exploration
issues such as the discovery of accidental artefacts. The confluence of
computing and statistics in some areas provides a nice backdrop against
which to examine these issues, and we briefly discuss neural networks and
classification trees from these two perspectives.
Dr. David Hand is Professor of Statistics at the Open University. His
research interests include the foundations of statistics, statistical
computing, and multivariate statistics, the latter especially as applied to
classification problems. His applications interests include medicine,
finance, and psychology. He is Editor-in-Chief of Statistics and Computing
and has has published fourteen books, the most recent of which is
Construction and Assessment of Classification Rules, Wiley, January 1997.
Tutorial 3: 10:30am-12:30pm
Text Mining - Theory and Practice
Ronen Feldman, Bar-Ilan University, Israel
Knowledge Discovery in Databases (KDD) focuses on the computerized
exploration of large amounts of data and on the discovery of interesting
patterns within them. While most work on KDD has been concerned with
structured databases, there has been little work on handling the huge
amount of information that is available only in unstructured textual form.
In this tutorial we will present the general theory of Text Mining and will
demonstrate several systems that use these principles to enable interactive
exploration of large textual collections. We will describe generic
techniques for text categorization and information extraction that are used
by these systems. The systems that will be presented are KDT which is the
system for Knowledge Discovery in Texts; FACT, which discovers associations
among keywords labeling the items in a collection of textual documents; and
the Text Explorer, which is a system that provides a high level language
for interactive exploration of textual collections. We will present a
general architecture for text mining and will outline the algorithms and
data structures behind the systems. We will give special emphasis to
incremental algorithms and to efficient data structures.
Dr. Ronen Feldman is a lecturer at the Mathematics and Computer Science
Department of Bar-Ilan University in Israel. He received his B.Sc. in Math,
Physics and Computer Science from the Hebrew University, and his Ph.D. in
Computer Science from Cornell University. His main research is in the area
of Machine Learning and Data Mining. He is currently coordinating several
research projects for developing dedicated text mining systems. These
systems work on plain text collections and on the Internet.
Tutorial 4: 1:30-3:30pm
Exploratory Data Analysis using Interactive Dynamic Graphics
Deborah Swayne, Bell Communications Research and Diane Cook, Iowa State
University
Researchers and software designers in the field of data mining are just
beginning to make extensive use of graphical methods. Interactive dynamic
data visualization has been explored in the field of statistics for over
twenty years, and we propose that much of what has been learned in
statistics is relevant for data mining. This class is an introduction to
interactive data visualization as it is practiced as part of exploratory
data analysis. The XGobi software, publicly available dynamic visualization
software, will be used in the analysis of examples from biology, business,
physics, engineering, and telecommunications. The examples will illustrate
a set of general visualization principles which are embodied in specific
methods such as brushing and identification of points in simple
scatterplots, three dimensional rotations, rotations in higher dimensions
such as the grand tour, and directed searches in higher dimensions for
interesting two dimensional views using projection pursuit and manual
control.
Deborah Swayne has worked at Bellcore since that company's inception in
1985, and is currently a member of the Statistics and Data Mining Research
Group. Her research focusses on software methods for visualizing data. She
is one of the authors of the XGobi software, originally developed at
Bellcore. She has a Bachelor's degree in African Linguistics from the
University of Wisconsin at Madison, and a Master's degree in Statistics
from Rutgers University.
Dr. Dianne Cook is an Assistant Professor in the Department of Statistics,
Iowa State University. She received her PhD from Rutgers University in May
1993, and has conducted research into dynamic statistical graphics. Her
interests include using these methods for understanding high-dimensional
data, and adapting them for analyzing geographically referenced data with
multiple measurements at each site.
Tutorial 5: 1:30-3:30pm
OLAP and Data Warehousing
Surajit Chaudhuri, Microsoft Research and Umesh Dayal, Hewlett Packard
Laboratories
On-Line Analytical Processing (OLAP) and Data Warehousing technologies
enable enterprises to gain competitive advantage by exploiting the
ever-growing amount of data that is collected and stored in corporate
databases and files for better and faster decision making. Over the past
few years, these technologies have experienced explosive growth, both in
the number of products and services offered, and in the extent of coverage
in the trade press. Vendors (including all database companies) are paying
increasing attention to all aspects of decision support. The area opens up
interesting research directions, with ties to past work in database
systems, but with different assumptions and requirements. Only very
recently, however, has the database research community started to
understand and address some of these issues. This tutorial presents an
overview of OLAP and data warehousing, and an in-depth study of selected
aspects. An outline of the tutorial follows:
1. Introduction: definitions, evolution, differences from OLTP,
architectures 2. Models and Tools: conceptual model for OLAP, front-end
tools (e.g., multidimensional spreadsheets), database design (e.g., star
and snowflake schema). 3. Database Server technologies for Decision Support
Queries: specialized indexing techniques, specialized join and scan
methods, data partitioning and use of parallelism, intelligent processing
of aggregates, complex query processing, extensions to SQL, ROLAP vs.
MOLAP. 4. Other Services for OLAP/Data warehousing: data cleaning, loading
and refresh, tools for warehouse, system and process management, metadata
management and the role of repository. 5. State of Commercial Practice. 6.
Research Issues. The target audience is researchers and developers
interested in learning about the concepts, products and the technical
innovations in the area of decision support technologies.
Dr. Surajit Chaudhuri is a researcher in the Database Research Group of
Microsoft Research. From 1992 to 1995, he was a Member of the Technical
Staff at Hewlett-Packard Laboratories, Palo Alto. He did his B.Tech at the
Indian Instiute of Technology, Kharagpur and his Ph.D. at Stanford
University. In addition to query processing and optimization, Surajit is
interested in the areas of data mining, database design and uses of
databases for nontraditional applications.
Dr. Umesh Dayal is a senior researcher at Hewlett-Packard Labs, Palo Alto,
California. His current research interests are in distributed information
systems, workflow management, data mining, and information management
issues related to the emerging global information infrastructure. He
received his Ph.D. and S.M. degrees from Harvard University, his M.E. and
B.E. degrees from the Indian Institute of Science, and his B.Sc. degree
from Osmania University, India.
Tutorial 6: 4:00-6:00pm
Visual Techniques for Exploring Databases
Daniel Keim, University of Munich
For data exploration to be effective, it is important to include the human
in the exploration process and combine the flexibility, creativity, and
general knowledge of the human with the enormous storage capacity and the
computational power of today's computers. Visual database exploration aims
at integrating the human in the exploration process, applying its
perceptual abilities to the large data sets available in today's computer
systems. The basic idea of visual data exploration is to present the data
in some visual form, allowing the human to get insight into the data and
draw conclusions. Visual data exploration techniques have proven to be of
high value in exploratory data analysis and they also have a high potential
for exploring large databases. Visual database exploration is especially
powerful for the first steps of the data mining process, namely
understanding the data and generating hypotheses about the data, but it may
also significantly contribute to the actual knowledge discovery by guiding
the search using visual feedback. The goal of the tutorial is to show the
potential of visualization technology for exploring large databases. The
tutorial provides an overview of the state-of-the-art in data visualization
and provides a classification of the existing data visualization
techniques. Besides describing each of the classes, the tutorial focuses on
new developments in data visualization, which are relevant to the area of
knowledge discovery, and describes a wide range of recently developed
techniques for visualizing large amounts of arbitrary multi-attribute data
which does not have any two- or three-dimensional semantics and therefore
does not lend itself to an easy display. A detailed comparison shows the
strength and weaknesses of the existing techniques and reveals potentials
for further improvements. Several examples demonstrate the benefits of
visualization techniques for exploring databases. The tutorial concludes
with an overview of existing database exploration and visualization
systems, including research prototypes as well as commercial products.
Dr. Daniel Keim is one of the leading experts in the field of visual
database exploration, and he was the chief engineer in designing the VisDB
system - a visual database exploration system. Dr. Keim received his
diploma (equivalent to an MS degree) in Computer Science from the
University of Dortmund in 1990 and his Ph.D. in Computer Science from the
University of Munich in 1994. Currently, he is a teaching and research
assistant (approximately equivalent to an assistant professor) at the
Institute for Computer Science of the University of Munich, Germany.
Tutorial 7: 4:00-6:00pm
Statistical Models for Categorical Response Data
William DuMouchel, AT&T Research
This tutorial will survey the most common models and methods statisticians
use to fit and test relationships among categorical (discrete) data. Most
of these techniques are described in statistics texts such as Categorical
Data Analysis , by Alan Agresti, (Wiley 1990) and are widely available in
popular computer packages such as SAS and Splus. Therefore it is almost de
rigeur for someone with a new classification technique to compare the
proposal to one or more of these standard methods. The tutorial will focus
on loglinear and logistic regression models, and related models such as
probit, poisson regression, and survival models. In the short time
available, priority will be given to explaining why these techniques are so
popular among statisticians, and to how the basic models have been extended
to handle variables having more than two categories or when some of the
variables have continuous or ordinal scales. Examples of model fitting,
model search and model comparison using SAS and Splus will be presented and
discussed.
Dr. William DuMouchel has been on the faculties of UC Berkeley, University of
Michigan, University of London, MIT and Columbia University. From 1987 to
1992 he was Chief Statistical Scientist at BBN Software Products, helping
to design and develop commercial software advisory systems for data
analysis and experimental design. He is currently at AT&T Labs - Research,
Florham Park, New Jersey.
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Date: Thu, 24 Apr 1997 18:06:38 -0400
From: samy@iss.gm.com
(R. Uthurusamy)
Subject: KDD-97 Workshop
KDD-97 Workshop - August 17, 1997 8:30am-5pm
---------------------------------------------
Issues in the Integration of Data Mining and Data Visualization
---------------------------------------------------------------
Details:http://www.cs.uml.edu/~grinstei/kddvis-workshop.html
Data visualization deals with the effective portrayal of data with a goal
towards insight about the data. Typically, the data is of high volume,
multidimensional in nature, and does not lend itself to easy display. The
data is also often non-spatial and temporal in nature.
Data visualization software systems are very popular with end-user domain
scientists who require visual tools to explore and analyze their data.
These visual tools however are used strictly as output of the exploration
process and have received much attention whereas the input issues to the
exploration process still have not. The KDD community is concerned with two
aspects of visualization techniques: 1. Its use at the 'back-end' of the
exploration process to help understand models extracted by data mining
algorithms, and 2. Scalability issues in visualization: how do we make it
efficient in presence context of large databases where data access is
expensive. The visualization community looks at KDD and analytic methods
also as applications to generate displays. However, visualization can be
used as input to KDD and analytic tools; it can also be used to support
computational steering. An effective visualization front-end can guide a
data mining algorithm in its search and may result in much better and more
easily acceptable solutions. This workshop will continue the discussions
started at the first two workshops and focus on these and other issues that
make a case for integrating KDD and visualization technologies.
Two previous workshops (Siggraph '90 and Visualization '91) have dealt with
areas such as high-level requirements for data structures and access
software, and data visualization environments. The first and second
workshop on Database Issues for Data Visualization were held in 1993 and
1995 and explored the fundamental issues. A number of experimental,
prototype, and research systems were presented. The second workshop also
saw a beginning interest with data mining and visualization integration.
This trend, so significant in the commercial sector today, is in its
infancy and is in need of much research attention.
Position statements and papers are welcome on the following issues as they
relate to KDD and data visualization integration. We would like to keep
discussions focused on the end result, which is improving the integration
of data mining and knowledge discovery systems with visualization:
* Requirements Visualization places on Knowledge Discovery Systems
* Data Models and Access Structures
* Modeling the User - Tasks, Processes, Support Issues
* Advanced User Interfaces for Data Mining
* Visual Languages for Data Mining
* System Integration Issues
* Computational Steering for Data Mining
* Scalability to Large Databases
* Distributed, Heterogeneous Data Set Issues - Data and Computation Sharing
* Examples of Integrated Systems
* Applications of Integrated Systems
Workshop Paper Submissions (Deadline June 15)
Papers (and position papers to be expanded for final publication) are
solicited that present research results in the integration of data mining
and visualization. Papers should be limited to 5,000 words and may be
accompanied by NTSC video. These should describe some original research on
the particular subject, and how it fits in with the overall theme of the
workshop. Proper references should be cited.
Workshop Registration Fee
Registration forms will be sent to the accepted participants. There is a
single registration fee of US $100 which covers the workshop sessions,
preprints, and coffee breaks.
Workshop Organizers
Georges Grinstein
Institute for Visualization and Perception Research
University of Massachusetts at Lowell
Lowell, MA 01854, USA
Email: grinstein@cs.uml.edu
Fax: +1-508-934-3551 * Phone: +1-508-934-3627
Andreas Wierse
Institute for Computer Applications
Dep. Computersimulation and Visualization
Pfaffenwaldring 27
D-70550 Stuttgart, Germany
Email: wierse@rus.uni-stuttgart.de,
Fax: +49(0)711-682357 * Phone: +49-711-685-5796
Usama Fayyad
Microsoft Research
Redmond, WA 98052-6399, USA
Email: fayyad@microsoft.com
Fax: +1-206-936-7329 * Phone +1-206-703-1528
---------------------------------------------
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Date: Thu, 24 Apr 1997 18:06:38 -0400
From: samy@iss.gm.com
(R. Uthurusamy)
Subject: KDD-97 Demos/Exhibits of Knowledge Discovery Products
-----------------------------------------------------
Following the sucess of the demonstration sessions in previous KDD
conferences, the KDD-97 program will also include demonstrations of
knowledge discovery products, knowledge discovery applications and research
prototypes. Unlike previous demonstration sessions, we will clearly
differentiate between commercial product demonstrations and research
demonstrations.
We are inviting commercial vendors to exhibit at KDD-97. The exhibitor fee
for KDD-97 will be a nominal $250.00. Exhibitors will be provided with a
6ft table top. In this space vendors will be allowed to distribute product
or company literature, show product demonstrations and set up signage.
Vendors will have to bring all necessary hardware and software that they
will require for their demonstrations.
The exhibit area will be open during the following hours: Aug. 15th: 12:30-5pm
For your information total attendance at KDD-96 was 457. Of these 35% were
affiliated with universities and 65% were affiliated with industry. If you
would like to exhibit at KDD-97 please fill out the registration form and
send it along with the name of your Product(s) and/or Service(s) and a 200
word (maximum) Description of Product(s)/Service(s) to: AAAI, KDD-97
Exhibit, 445 Burgess Drive, Menlo Park, CA 94025, USA. The description
will be included in the conference program.
We are also soliciting demonstrations of research prototypes at KDD-97.
This demonstration session will be held on August 15 from 12:30 to 5:00
PM. We have a limited budget for providing hardware for research
demonstrations. This year we will give priority to demonstrations that are
in conjunction with accepted papers at KDD-97. Within budget and space
constraints we will make every effort to accommodate as many demonstrations
as possible. If you would like your demonstration to be considered for
KDD-97 please provide the following information to Tej Anand
(tej.anand@atlantaga.ncr.com)
by June 1, 1997.
* Name of Demonstration:
* Title of Paper: (If this demonstration is in conjunction with a
paper/poster at KDD-97)
* Development Team:
* Affiliations of Development Team Members:
* Contact Telephone#:
* Description of Demonstration: (A short description of approx. 200 words)
* What is unique about your system or application?: (No more than 50 words)
* Status: Research Prototype/Commercially available product/Fielded application
* Hardware Required: (Please state any special memory or disk requirements)
* Operating System: (Please state specific version number)
* WAN Connection Required: Yes/No
(If Yes, please state any special modem requirements)
* Will you bring your own hardware?: Yes/No
* Any other requirements:
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Date: Thu, 24 Apr 1997 18:06:38 -0400
From: samy@iss.gm.com
(R. Uthurusamy)
Subject: KDD-97 Registration Information
A registration application is attached to this online brochure. The KDD-97
program registration includes admission to four tutorials, 4 tutorial
syllabi, technical and demo sessions, the opening reception, the KDD-97
Conference Proceedings and mid-morning & afternoon coffee breaks. Onsite
registration will be located in the foyer outside the California Ballroom,
Newport Beach Marriott Hotel and Tennis Club, lobby level.
Early Registration (Postmarked by June 10)
AAAI Members
Regular $295 Students $95
Nonmembers
Regular $375 Students $155
Late Registration (Postmarked by July 15)
AAAI Members
Regular $350 Students $125
Nonmembers
Regular $425 Students $180
On-Site Registration (Postmarked after July 15 or onsite.)
AAAI Members
Regular $400 Students $475
Nonmembers
Regular $150 Students $210
Workshop Registration
Registration forms will be sent to the accepted participants. There is a
separate registration fee of US $100 which covers the workshop sessions,
preprints, and coffee breaks.
Payment Information
Prepayment of registration fees is required. Checks, international money
orders, bank transfers and travelers' checks must be in US dollars.
American Express, MasterCard, VISA, and government purchase orders are also
accepted. Registration applications postmarked after the early
registration deadline will be subject to the late registration fees.
Registration applications postmarked after the late registration deadline
will be subject to on-site registration fees. Student registrations must be
accompanied by proof of full-time student status.
Refund Requests
The deadline for refund requests is July 25, 1997. All refund requests
must be made in writing. A $75.00 processing fee will be assessed for all
refunds.
Registration Hours
Registration hours will be Thursday-Saturday, August 14-16, 7:30am-6:00pm
and Sunday, August 17, 8:00am-3:00pm. All attendees must pick up their
registration packets for admittance to programs.
Housing
AAAI has reserved a block of rooms at the Newport Beach Marriott Hotel at
reduced conference rates. Conference attendees must contact the hotel
directly and identify themselves as KDD-97 registrants to qualify for the
reduced rates. Hotel rooms are priced as singles (1 person, 1 bed),
doubles (2 persons, 2 beds), triples (3 persons, 2 beds), quads (4 persons,
2 beds). Rooms will be assigned on a first-come, first-served basis. All
rooms are subject to a 10% occupancy tax.
Headquarters Hotel:
Newport Beach Marriott Hotel
900 Newport Center Drive
Newport Beach, CA 92660
Phone: 714-640-4000
Fax: 714--640-4918
Single room: $105.00
Double room: $115.00
Check-in time: 4:00pm
Check-out time: 12:00 noon
Cut-off date for reservations: July 24, 1997.
All reservation requests for arrival after 6:00 pm must be accompanied by a
first night room deposit, or guaranteed with a major credit card. The
Newport Beach Marriott Hotel will not hold any reservations after 6:00 pm
unless guaranteed by one of the above methods. Reservations received after
the cut-off time will be accepted on a space or rate available basis.
Reservations accepted without a credit card guarantee or advance deposit
are subject to cancellation at 6:00 pm on the day of arrival.
Air Transportation and Car Rental
Newport Beach, California - Get there for less!
Discounted fares have been negotiated for this event. Call Conventions in
America at 1-800-929-4242 and ask for Group #428. You will receive 5%-10%
off the lowest applicable fares on American Airlines, or the guaranteed
lowest available fare on any carrier. Travel between August 11-21, 1997.
All attendees booking through CIA will receive free flight insurance and be
entered in their bi-monthly drawing for worldwide travel for two on
American Airlines! Hertz Rent A Car is also offering special low
conference rates, with unlimited free mileage.
Call Conventions in America - 1-800-929-4242, ask for Group #428.
Reservation hours: M-F 6:30am-5:00pm Pacific Time.
Outside US and Canada, call 619-453-3686/Fax 619-453-7679.
Internet: scitravel@aol.com/24-hour
emergency service 1-800-748-5520.
If you call direct: American 1-800-433-1790, ask for index #S 9485.
Hertz 1-800-654-2240, ask for CV#24250.
Ground Transportation
The following information provided is the best available at press time.
Please confirm fares when making reservations.
Airport Connections
The Newport Beach Marriott Hotel provides complimentary airport
transportation to/from John Wayne /Orange County Airport.
Super Shuttle: 714-517-6600. The fare from LAX Los Angeles International
Airport to Newport Beach Marriott Hotel is $21.00 per person. Reservations
24 hours in advance are recommended. Discover Card, traveller's checks and
cash is accepted.
Taxi
Taxis are available at John Wayne Airport. Approximate fare from the
airport to downtown Newport Beach is $14.00. Orange County Yellow Cab
Service: 714-546-1311. The approximate taxi fare from LAX Los Angeles
International Airport to Newport Beach Marriott Hotel is $75.00-80.00.
Bus
Greyhound/Trailways Lines. The depot is located at 100 W. Winston Road,
Anaheim, CA 92805. For information on fares and scheduling, call
714-999-1256.
Rail
The Amtrak (Southern Pacific Railroad) stations are located at Santa Ana,
Irvine and Anaheim. For general information and ticketing, call
1-800-872-7245.
City Transit System
OCTD (Orange County Transit District) serves Newport Beach, Balboa Island
and Corona del Mar. Basic local fare is $1.00. For general information
call 714-636-RIDE.
Parking
Parking is available at the Newport Beach Marriott Hotel. The daily rate
for valet parking is $6.00, and $8.00 overnight. Self-parking is
complimentary.
Disclaimer: In offering American Airlines, Hertz Rent A Car, Newport Beach
Marriott Hotel, and all other service providers, (hereinafter referred to
as 'Supplier(s)' for the Third International Conference on Knowledge
Discovery and Data Mining, AAAI acts only in the capacity of agent for the
Suppliers which are the providers of the service. Because AAAI has no
control over the personnel, equipment or operations of providers of
accommodations or other services included as part of the KDD-97 program,
AAAI assumes no responsibility for and will not be liable for any personal
delay, inconveniences or other damage suffered by conference participants
which may arise by reason of (1) any wrongful or negligent acts or
omissions on the part of any Supplier or its employees, (2) any defect in
or failure of any vehicle, equipment or instrumentality owned, operated or
otherwise used by any Supplier, or (3) any wrongful or negligent acts or
omissions on the part of any other party not under the control, direct or
otherwise, of AAAI.
Newport Beach, California!
Newport Beach is located along the beautiful Pacific Ocean in Orange
County, California, nestled south of Los Angeles, north of San Diego,
southwest of Disneyland in Anaheim, and adjacent to John Wayne/Orange
County Airport. Surrounded by one of the largest small-boat harbors in the
world and lazily stretching itself along more than six miles of scenic
Pacific coastline, Newport Beach beckons national and international
visitors to moor at the magnificient harbor and discover 'The Colorful
Coast'.
Newport Beach Visitor Information
A Concierge Desk is available in the Newport Beach Marriott Hotel. They
can assist with dining reservations, directions, tour bookings,
entertainment suggestions, and transportation information. Maps and
brochures are available.
URL:http://www.newport.lib.ca.us/NBCVB/NBCVB.html
************************************************************************
KDD-97 PREREGISTRATION APPLICATION
Name:
Company/Univ:
Dept/MS:
Address (Specify Home or Business):
City:
State:
Zip:
Phone & FAX:
Membership No:
Email Address:
************************************************************************
TECHNICAL PROGRAM (Includes Proceedings)
EARLY REGISTRATION LATE REGISTRATION
(postmarked by June 10) (postmarked by July 15)
AAAI Member Nonmember AAAI Member Nonmember
Regular Student Regular Student Regular Student Regular Student
$295 $95 $375 $155 $350 $125 $425 $180
(Students must send proof of student status to the AAAI Office. By joining
AAAI now, you can qualify for member rates. Membership information is
available from membership@aaai.org
orhttp://www.aaai.org.
Total KDD-97 Conference Fee: ______
************************************************************************
TUTORIAL PROGRAM
Thursday, August 14
(Conference fee includes up to 4 consecutive tutorials & accompanying syllabi)
8:00-10:00 AM T1
10:30 AM-12:30 PM T2, T3
1:30-3:30 PM T4, T5
4:00-6:00 PM T6, T7
Please list selected tutorial codes:
************************************************************************
KDD-97 Workshop
Sunday, August 17
$100 per person.
Total Workshop Fee: _______
************************************************************************
KDD-97 OPENING RECEPTION (Included in technical program registration)
Fee for spouse, child, or guest is $20 per person.
Total reception fee: ______
************************************************************************
Exhibit Registration
August 15, 1997
$250 per exhibitor. An exhibitor kit will be mailed upon receipt of
registration.
Total Exhibitor Fee: _______
************************************************************************
PAYMENT
Email registrations must be accompanied by a credit card number.
Total Amount Due: ______
Check one: Mastercard ___ Visa ___ American Express ___
Credit Card Account Number:
Expiration Date:
Name as it appears on card:
Forms cannot be processed if information is incomplete. The refund request
deadline is July 25, 1997. A $75.00 processing fee will be assessed for
refunds.
Registrations postmarked after July 15 are subject to onsite rates.
Mail completed application to kdd@aaai.org
or fax to 415/321-4457.
Please note that there are security issues involved with the transmittal
of credit card information over the internet. AAAI will not be held liable
for any misuse of your credit card information during its transmittal
from you to AAAI.
For complete KDD-97 information, please visit AAAI's web site at
http://www.aaai.org.
Thank you for your registration! See you at KDD-97
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Date: Thu, 24 Apr 1997 08:42:49 -0400
From: peter@ai.iit.nrc.ca
(Peter Turney)
Subject: Re: data mining from wafers manufacturing process
Dear Elisa:
> At our University, we are starting an application project
> dealing with data from a wafers manifacturing process.
> We are thinking to use data mining techniques
> for try to address the following problem.
> Some of those wafers are faulty. There is a database keeping track
> of the entire manifacturing process for each wafer and collecting
> large amount of data concerning each step of the manifacturing
> process (there are about 300 steps; each step is characterized
> about 100 parameters). Our problem is use data mining techniques
> in helping the diagnosis, that is, to see which step
> may have caused the problem.
>
> I was wondering whether you are aware of any use of data mining
> techniques for similar problems. We have also to acquire
> some suitable data mining tools.
Here are two relevant URLs for you:
1.ftp://ai.iit.nrc.ca/pub/iit-papers/NRC-39163.ps.Z
P. Turney. Data Engineering for the Analysis of Semiconductor
Manufacturing Data. IJCAI-95 Workshop on Data Engineering for
Inductive Learning: 50-59. 1995.
2.http://www.quadrillion.com/
Quadrillion Corporation, makers of Q-Yield
Best wishes,
Peter.
http://ai.iit.nrc.ca/staff/peter.html
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From: bissantz@bissantz.de
Date: Thu, 24 Apr 97 11:18:57
Subject: FW: new entry for siftware section
Siftware: Delta Miner
*URL: http://www.bissantz.de
*Description::
Delta Miner 3.0 is a suite of easy to handle data mining instruments for
financial controlling applications
and database analysis.
*Discovery tasks: Clustering, Summarization,
Deviation Detection, Visualization
*Comments: Delta Miner 3.0 is a suite of data mining
instruments that analyzes complex data pools. Delta Miner's tools are
flexible: they lend themselves to a broad range of applications. A
common application is the analysis of financial controlling data. Delta
Miner guides the user quickly and easily through complex data structures
down to the significant facts. In contrast to the simple 'Drill-down'
capabilities of typical EIS and MIS tools, Delta Miner integrates a high
level of helpful automation. The system is capable of recommending the
best analysis paths, thereby relieving the controller from tedious
routine tasks. In addition to identifying the important trends, the tool
also points to the causes of those trends. Further analyses inform the
user about the best possible countermeasures to negative developments.
The basis techniques of the Delta Miner were developed at FORWISS, where
since 1993, a research group led by Prof. Dr. Peter Mertens has
intensively investigated algorithms for Data Mining. At it's first
presentation delta miner was recognized as one of the best three
products in the category 'Business Management Solutions' at the Systems
'96 trade show in Munich. A demoversion can be downloaded.
*Platform(s): Windows 95, NT
*Contact:
Bissantz K�ppers & Company GmbH
Am Weichselgarten 7
91058 Erlangen
Germany
phone +49 9131 691-450
fax +49 9131 691-455
service@bissantz.de
*Status: Product
*Updated: 1997-04-11 by Dr. Nicolas Bissantz (bissantz@bissantz.de)
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Date: Wed, 30 Apr 1997 16:22:28 -0400
From: Pablo Tamayo (tamayo@think.com)
Job Description:
Staff Member in the Technology Group
Researcher/Developer of Data Mining/KDD Technologies
Thinking Machines Corp.
4/30/97
- Provide technical and scientific expertise in core areas for Data
Mining and KDD, such as Machine Learning, Artificial Intelligence,
Statistics and High Performance Computing, to the development
organization and the company in general. Help to evaluate competing, new
or strategic technologies and algorithms for current or future releases
of Data Mining/KDD products (toolsets, KDD engines and vertical
applications).
- Design and develop state-of-the-art Machine Learning/Statistical
module prototypes. Be responsible for the support and maintenance of the
assigned modules. Collaborate with the Software Engineering Group
to integrate these prototypes into products' software architecture
following development-wide software engineering guidelines. Provide
parallelism and performance enhancements for algorithms. Help support
core algorithms in current products.
- Collaborate with the Data Analysis, Professional Services and
Technical Sales groups to study and choose appropriate algorithms and
methods for proof of concept studies or to integrate permanent solutions
for customers.
- Help write patents and provide technical assistance in patent related
issues.
- Represent the company in relevant conferences, workshops, trade shows
or forums and follow Data Mining/KDD literature and trends in the KDD
academic and commercial communities.
If you are interested please contact:
Dr. Pablo Tamayo
tamayo@think.com
Thinking Machines Corp.
14 Crosby Dr.
Bedford, MA 01730
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From: Eric Horvitz (horvitz@MICROSOFT.com)
Date: Wed, 23 Apr 1997 13:53:39 -0700
Thirteenth Conference on Uncertainty in Artificial Intelligence
Please refer to the UAI '97 home page athttp://cuai97.microsoft.com
for
updated information on this summer's UAI conference and registration
procedures. UAI will follow right after AAAI in Providence. The page
also includes other information of interest, including details (...and
even some reading assignments) for the UAI '97 Full Day Course on
Uncertain Reasoning on Thursday, July 31. The pages also contain
information on accomodations in Providence.
Looking forward to seeing you this summer,
Eric Horvitz
Conference Chair
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From: agent@ahcsun1.heuristics.com
Date: Fri, 25 Apr 1997 14:45:21 -0400
Subject: The Gordian Institute's 'Making Sense of Data: Computer-Aided
Pattern Discovery' course is scheduled for July 14-18 in
Charlottesville, Virginia. Refer tohttp://www.gordianknot.com
------------------------------------------------------------------------
The Gordian Institute, a division of American Heuristics Corporation (AHC),
established July 14-18, 1997 in the historic town of Charlottesville near
Monticello as the venue for the next offering of 'Making Sense of Data:
Computer-Aided Pattern Discovery.'
The intensive four and one-half day data mining course will take place in
Charlottesville, Virginia with a start date of July 14, 1997. The course
includes live interactive demonstrations using data from real-world
applications. Participants need only have prior working experience with
computers and familiarity with data related problems to benefit from the
course.
Attendees will explore a host of advanced computing techniques and software
tools used to discover useful patterns hidden in data. The course surveys
modern algorithms drawn from the fields of statistics, machine learning, data
mining and inductive modeling which automatically build classifiers or
estimators from a database. You may never find another course that succinctly
covers the essential parts of so many aspects of 'data mining' with both
theoretical and practical insights. Topics to be presented are:
-Pattern Discovery: An Overview
-Inducing Models from Data: Benefits and Dangers
-The Data Mining Process
-Perspectives of Related Fields:
-Statistics, Machine Learning, Data Mining
and Artificial Intelligence
-Data Issues
-Case Diagnostics (Outlier, Influential, Leverage Points)
-Feature Creation and Selection
-Classical Statistical Techniques
-Linear: Regression and Discriminant Analysis
-Nonparametric: Scatterplot Smoothers,
Nearest Neighbors, Kernels
-Key General Tools:
-Scientific Visualization
-Resampling
-Optimization
-Clustering
-Modern Methods
-Neural Networks
-Polynomial Networks (ASPN, AIM)
-Decision Trees (CART)
-Brief Survey of Other Methods
-Projection Pursuit
-ASH (Average Shifted Histograms)
-MARS (Multivariate Adaptive Regression Splines)
-Radial Basis Functions
-Comparing and Combining Methods
While increasingly awash in data, most organizations are unable to fully
extract the useful information embedded within. The practical techniques
taught in this course can help you to discover and make sense of hidden
patterns. A key element of corporate efficiency must be the extraction of
important information to support the decision making process and accurately
predict and plan for future needs. Those from government, industry and
academia who see the need for non-linear modeling techniques, and who have
particular applications not adequately solved with classic modeling techniques
are target candidates for this course.
Direct Quote from Course Evaluation Sheet:
'I felt this course was far superior to many others that I have been exposed
to. Most notably, the instructors were not only clearly experts but were not
biased toward any one software package or technique. The instructors also
emphasized targeting the users' specific applications (including analyzing
sample data brought in by the students). This is exceptionally useful. Great
value for the $. What was most valuable to me was the presentation of a broad
range of both analytical techniques and software tools for solving various
problems. This helps to give me the 'big picture' and allows me to best
determine what technologies are most applicable and useful to me.'
-Andy Kalish, Eastman Kodak
The Instructors:
John F. Elder IV, PhD, and Dean Abbott of Quantitative Solutions explain the
methods used inside leading commercial and academic software, providing
practical tips and techniques on feature extraction and neural network problem
solving. The course instructors each have more than a decade of experience in
applying adaptive, data-driven techniques to practical problems.
Dr. Elder has developed or refined some of the methods covered in this course.
He is Chief Scientist at Quantitative Solutions and Adjunct Professor at the
University of Virginia, and has authored four book chapters and numerous
articles on adaptive methods of pattern discovery. He has been a researcher
at Rice University and at an engineering consulting firm, and was Director of
Research for an investment management company. Dr. Elder is a frequent
lecturer on pattern discovery techniques, and is the technical chair of the
Adaptive and Learning Systems Group of the IEEE Systems, Man, and Cybernetics
Society.
Dean W. Abbott is a Senior Research Scientist at Quantitative Solutions. He
has applied data mining techniques to challenges in optimum guidance and
control, optical character recognition, image pattern recognition, and radar
and multi-spectral signal processing. Mr. Abbott has developed pattern
recognition software that is sold commercially, and has written and lectured
on novel applications of feature selection, polynomial network, and pattern
recognition techniques to solve real-world problems in several fields.
Pricing Information:
Registration for this four and one-half day course is $1995. Government and
academic discounts may apply. Lodging details and directions may be viewed at
http://www.gordianknot.com,
or obtained by providing a fax number or Email
address to (800) 405-2114 or agent@gordianknot.com.
You may also send a
message to agent@gordianknot.com
with 'newsletter' in the subject field to
receive a quarterly electronic newsletter from The Gordian Institute.
If you have remaining questions regarding the course, a knowledgeable
representative may be contacted directly at (800) 405-2114. Seats may also be
secured through Gordian's web site. Space is limited to 24 seats, so go to
your browser, set it tohttp://www.gordianknot.com
and reserve your place!
__________________________
The Gordian Institute
http://www.gordianknot.com
agent@gordianknot.com
(800) 405-2114
__________________________
The parent company, American Heuristics Corporation (AHC) is a founding member
of the West Virginia High Technology Consortium, with headquarters in
Triadelphia, West Virginia. AHC is an advanced software technology consulting
company applying hybrid software solutions to complex technical problems in
business, industry and government. AHC may be found on the web at:http://
www.heuristics.com
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From: 'Prof. Zicari' (zicari@informatik.uni-frankfurt.de)
Date: Sun, 27 Apr 1997 00:10:18 +0200 (METDST)
I would like to inform you that the conference programs of
COMDEX Internet & OBJECT WORLD Frankfurt`97 (October 7-10)
are now available on line at :
http://www.ltt.de
The web site will be updated on a regular base.
If you have any questions, please send me an e-mail at
roberto_zicari@omg.org.
Best Regards
Roberto Zicari
Chair Advisory Board,
COMDEX Internet & OBJECT WORLD Frankfurt.
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