News: *
GPS, New Section in KD Nuggets: Industry-Specific Solutions *
Alan Beck, New e-Newsletter: D S *, the On-line Executive Journal
for Data-Intensive Decision Support *
Andrew Braunberg, New Publication: Data Mining News,
Positions: *
Peter A. Flach, Visiting research fellowship in ILP at Bristol, UK *
Yuri Owechko, Research position at Hughes Research Laboratories, CA *
R. King, Univ. of Wales, UK, Research Associate
Meetings: *
Andy Hilford, The Evolution of Data Mining: Technical Strategies
to Beat your Competition by the Year 2000, New York City,
Oct 23-24, 1997,
--
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.
KD Nuggets frequency is 2-3 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 KD Nuggets web site
at
********************* Official disclaimer ***************************
All opinions expressed herein are those of the contributors and not
necessarily of their respective employers (or of KD Nuggets)
*********************************************************************
~~~~~~~~~~~~ Quotable Quote ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
George Chapman. 1557-1634.
... Each natural agent works but to this end,--
... To render that it works on like itself.
Previous1NextTop
Date: Fri, 12 Sep 1997 12:51:36 -0400
From: GPS (gps)
Subject: New Page in KDNuggets web site: Industry-Specific Solutions
The universe of data mining tools is rapidly expanding and many systems
which do data mining and knowledge discovery embed the data mining engine
inside a complete solution for a specific business
problem, such as credit-card fraud detection, cellular phone cloning,
or mortgage approval.
Such systems have recently appeared in many information-intensive business sectors, including
banking/finance
data quality analysis
health care
insurance
internet
investment
retail
sports and entertainment
telecommunications
travel and transportation
I am soliciting brief descriptions of such industry-specific data-mining based systems
for these and other sectors, for a new page of www.kdnuggets.com web site.
Please email to gps
a brief (300 words or less) description of such systems,
using the following template:
* For a free trial subscription, email: dstrial@tgc.com
*
__________________________________________________________
While there are many sources of information covering issues related to
- Data Warehousing,
- Data Mining,
- Decision Support,
- On-Line Transaction Processing (OLTP),
- On-Line Analytic Processing (OLAP),
- And a host of related topics,
confusion about profitable leveraging of these technologies has never been
greater. A high-level executive journal, D S * (star), has been created
for professionals who need concrete, proven strategic guidance through
this morass of facts and figures. D S * features analysis, commentary and
specific guidance from renowned experts who have shown firms how to
extract financial benefit from very large data sets. Now D S * will bring
these executive insights to you weekly in a concise digital format.
The first issue of D S * will appear Oct. 7. Please accept our invitation
for a free trial subscription to this timely, relevant and insightful new
executive journal.
* For a free trial subscription, email: dstrial@tgc.com
*
__________________________________________________________
Sincerely,
Thomas Tabor Alan Beck
Publisher Editor In Chief, D S *
Postscript: About the Name D S *
----------------------------------
D S stands for decision support, the single concept dynamically
underlying technologies designed to extract maximum value from very large
databases, e.g. data mining, data warehousing, knowledge discovery, OLAP,
etc. The * (pronounced 'star') signifies both that which is preeminent and
the UNIX command for universal application. (Thus, if the command-line
'rm *' is entered into a UNIX system, every file in that directory will be
removed.) In addition, the star schema holds a vital position in the
discipline of data modeling for data warehouses. Together, the ideas
giving rise to these symbols create a designation as unique and exclusive as
the publication itself.
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Alan Beck 8445 Camino Santa Fe
Vice President, Publications San Diego, CA 92121
alan@tgc.com
PH (619) 625-0070
T A B O R G R I F F I N C O M M U N I C A T I O N S
---------------------------------------------------------
HPCwire * WEBster * INTERNET PUBLISHING SOLUTIONS
Previous3NextTop
Date: Sat, 06 Sep 1997 09:10:08 +0000
From: Andrew Braunberg (abraunberg@idagroup.com)
Subject: Data Mining News
URL: www.idagroup.com
The first issue of Data Mining News was published Sept. 1. This
bi-weekly newsletter provides news and analysis of the knowledge
discovery/decision support industry. Data Mining News is published by
the Bethesda, Maryland-based Intelligent Data Analysis Group (IDAG). We
are committed to providing timely, actionable information to our
readers.
Data Mining News tracks market trends, strategic alliances and
acquisitions, new products and pricing strategies, contracts, and
applications. The first issue is viewable on-line (www.idagroup.com).
Data Mining News is being offered at an introductory price of $497 per
year (24 issues). A four issue trial subscription is available.
While there are numerous sources of impartial information in the
knowledge discovery research community, independent news and analysis is
scarce regarding commercial offerings and activities.
Data Mining News is targeted at executives who are looking for an
independent source of business information. We feel that Data Mining
News is an important addition to the industry, and will compliment
existing sources of information such as KDnuggets.
Best Regards,
Andrew Braunberg,
Editor, Data Mining News
Intelligent Data Analysis Group
4938 Hampden Lane
Number 340
Bethesda, MD 20814
301/770-3490
301/770-3491 fax
Previous4NextTop
Date: Fri, 12 Sep 1997 16:55:42 -0400
From: Steve Gallant (sgallant@kstream.com)
Subject: NBA and Data Mining
The Wall Street Journal Interactive Edition -- September 13, 1997
NBA Teams Look for Help
From the Digital Sixth Man
By GENE KOPROWSKI
Special to THE WALL STREET JOURNAL INTERACTIVE EDITION
AS THE National Basketball Association prepares for the opening of training
camp, some coaches think that data-mining applications could soon determine
which team wins a championship.
This 'digital sixth man' is a relatively new force in the NBA, but it's not
untested: The Orlando Magic, for one, credit the technology with helping it
fight back in the playoffs this past spring.
The Magic dropped its first two playoff games to the Miami Heat, as starting
guards Anfernee Hardaway and Brian Shaw delivered lackluster
performances on the court. In an effort to salvage the series, Orlando
assistant
coach Tom Sterner turned to his notebook personal computer and its
data-mining program.
'One of the key parts of a coach's job is match-up analysis,' says Mr. Sterner.
'Technology like data mining can really help with that.'
Searching through game statistics and player match-ups, Mr. Sterner's
algorithms discerned that when Messrs. Hardaway and Shaw, the starters,
were on the floor, the Magic trailed by as many as 17 points. But when
backup guard Darrell Armstrong replaced Mr. Shaw, the team had a 14-point
advantage. So for the next two games, the coaches dramatically increased Mr.
Armstrong's playing time, and Orlando evened the series.
'It was an astounding thing,' says Mr. Sterner.
It wasn't astounding enough -- Orlando would lose the series, 3-2 -- but data
mining and data warehousing, which together make up a multibillion dollar
industry that stretches from desktops to mainframes, is starting to make an
impact on professional sports that could be as big as it has been for other
industries.
Using algorithms, neural networks and other modeling tools, vendors like SAS
Institute Inc., International Business Machines Corp. and Data General Corp.
are helping corporate clients more effectively manage day-to-day operations,
target prospects, and plan promotions. Now they're also helping teams set
strategy -- both on and off the court.
'The technology is still pretty new, and it only recently evolved from R&D to
real, practical business use,' says Kay Hammer, CEO and president of
Evolutionary Technologies International, an Austin, Texas, data-warehousing
firm.
Coaches have turned to computers for years to find an edge in carefully stored
statistics. But when accessing all that data, they have been limited to ad hoc
queries -- coming up with hypotheses and looking through the stats to see if
their theory is sound. But in data mining, the application itself analyzes the data
to reveal patterns.
'Data mining lets you find something that you didn't know you were looking
for,' says J. D. Hicks, chief technology officer at Dallas systems integrator
Virtual Solutions Inc.
When Chicago Bulls star Michael Jordan retires and leaves the talent level in
the league roughly even, NBA coaching staff and observers agree that the
digital sixth man could tip the outcome of games -- or even the season.
'The application is worth at least a basket a game,' says Bob Salmi, assistant
coach of another team that utilizes the technology, the Dallas Mavericks.
'And all of these games are close.'
A partnership between IBM and the NBA is key to the increased use of the
data mining in basketball. But Clariion Corp., a division of Data General, is
working with the National Football League, and other data-mining companies
are working with professional baseball teams.
Researchers for IBM -- an official NBA sponsor -- teamed up with Messrs.
Salmi and Sterner about two years ago to develop a data-mining program
especially for the NBA. The idea was the same as that used in business
applications: extract meaningful information from large amounts of data.
The result of the collaboration, says IBM consultant Inderpal Bhandari, was
the development of an algorithm that performed so-called 'attribute
focusing,'
the systematic search for interesting patterns and statistical correlations.
'You can ask what-if queries, such as, 'Under what circumstances do the
Knicks manage to outscore the Bulls?' ' says Mr. Bandari. 'It is at that level
that the query is automatically conducted, as opposed to a traditional
database query which sought out Patrick Ewing's field-goal percentage.'
'We're moving,' he adds, 'to the stage of asking abstract questions.'
In an advance that really brought home the value of the technology to the
NBA, the statistical database was linked to a CD-ROM containing digitized
game footage. Coaches can run a query, see the statistical results, and
cue it to a time-stamped video of the game.
'It was more intriguing than it was useful, prior to that point,' says Mr. Salmi.
'Until you actually see the plays involved, it really doesn't make any sense.'
The technology came into its own, when the Magic used it effectively in the
playoffs last season. Though Orlando lost the series, the software -- which is
known as Advanced Scout, and runs on an IBM ThinkPad -- helped the team
salvage two games.
Only a handful of teams -- the Magic, the Mavericks, the Heat and the Bulls,
among them -- employ data mining actively in games today, although IBM has
furnished the entire league with the technology. The Bulls, in fact, have their
own $2 million system, based on Apple's Macintosh computers and
proprietary software algorithms.
'Michael Jordan and Scottie Pippen help, but we do our share here too,' says
the Bulls' video coach, Greg Sabourin. 'Why do you think we have such
strong third quarters?'
The data collected and the data-mining software's analysis is hardly going
unused. Coaches view the game tapes during halftime and after games; Mr.
Salmi, for one, stores data from the 2,378 games played during the league's
full season. Some teams run off scores of CDs in a manner of minutes after
games for distribution to coaching staff and key players.
What's more, the disparity between the NBA's techno-haves and its have-nots
is shrinking. In the coming weeks, the league will host a 'Technology Summit'
where teams will share their know-how.
'Some teams are technologically uneducated -- this is an effort to bring
everyone up to speed,' says Mr. Sterner. 'All things being equal, there has got
to be something that can make a difference in a game. I think technology can
make the difference.'
The NFL also is getting into the digital-database game. John Wuehrmann,
director of technology operations for the Kansas City Chiefs, says that last
season, the team installed a digital fiber-channel network and linked PC
workstations to show coaches an array of key plays from blitzes to
touchdowns.
Major League Baseball, meanwhile, has started using the software in the front
office. Jim Pappas, market-systems analyst for the Pittsburgh Pirates,
says the
team uses data mining to select target groups for season-ticket pitches. And
where sports is leading, the sports media is following: NBC Sports used data
mining during its coverage and post-game analysis of the NBA Finals.
Can technology really beat talent in professional sports? Will the digital sixth
man replace Michael Jordan as the most celebrated figure in the NBA in the
coming years? Some have their doubts. 'I find it hard to believe that a coach
would not rely on their own instincts and crouch down in a huddle in the
middle of the fourth quarter and pull out a laptop,' says Melissa Isaacson, a
sports columnist for the Chicago Tribune.
'Besides,' she adds, 'as a fan, I would rather have a human make an error that
could cost them the game than a computer.'
Mr. Salmi and others do think data mining can provide an edge, although they
admit that coaching skill must go far beyond reading spreadsheets and
discerning bits from bytes. 'This is just a tool, like other tools we use,' Mr.
Salmi says. 'Once you find something that helps your team, you are on a
journey of discovery. Half an hour later, in the middle of the game, you forget
where the hell you started.'
o KDD-CUP Competition
o KDD-CUP Process (includes links to the registration
brochure and the questionnaire)
o KDD-CUP Data Set
o Participant Statistics
o Software/Tool Statistics
o Algorithm Statistics
o Evaluation Criteria/Metrics
o KDD-CUP Results
o KDD-CUP Awards
o Going Forward: KDD-CUP-98
I'll appreciate if you could post this information to KDNuggets as
many people asked for a copy of the presentation.
Regards.
*-----------------------------*
| Ismail Parsa |
| Epsilon Data Management |
| 50 Cambridge Street |
| Burlington MA 01803 USA |
| |
| E-MAIL: iparsa@epsilon.com
|
| V-MAIL: (617) 273-0250*6734 |
| FAX: (617) 272-8604 |
*-----------------------------*
Previous6NextTop
Date: Mon, 08 Sep 97 10:39:15 -0700
From: 'Shivakumar Vaithaynathan' (shiv@almaden.ibm.com)
Subject: CFP: AI Review: Special Issue on Data Mining on the Internet
Artificial Intelligence Review:
Special Issue on Data Mining on the Internet
The advent of the World Wide Web has caused a dramatic increase in usage
of the Internet. The resulting growth in on-line information combined
with the almost chaotic nature of the web necessitates the development
of powerful yet computationally efficient algorithms to track and tame
this constantly evolving complex system.
While traditionally the data mining community has dealt with
structured databases, web mining poses problems not only due to the
lack of structure, but also due to the intrinsic distributed nature of
the data. Furthermore, mining on the Internet involves also dealing
with multi-media content consisting of not only natural language
documents but also images, audio and video streams. Several
interesting and potentially useful applications have already been
developed by academic researchers and industry practitioners to address
these challenges. It is important to learn from these initial endeavors,
if we are to develop new algorithms and interesting applications.
The purpose of this special issue is to provide a comprehensive
state-of-the-art overview of the technical challenges and successes
in mining of the Internet. Of particular interest are papers
describing both the development of novel algorithms and applications.
Topics of interest could include but are not limited to:
* Resource Discovery
* Collaborative Filtering
* Information Filtering
* Content Mining (text, images, video, etc.)
* Information Extraction
* User Profiling
* Applications, e.g., one-to-one marketing
In addition to the call for full-length papers, we request that any
researchers working in this area submit abstracts and/or pointers to
recently published applications for the purposes of compiling a
comprehensive survey of the current state-of-the-art.
The mission of Artificial Intelligence Review: The Artificial
Intelligence Review serves as a forum for the work of researchers and
application developers from Artificial Intelligence, Cognitive Science
and related disciplines. The Review publishes state-of-the-art
research and applications and critical evaluations of techniques and
algorithms from the field. The Review also presents refereed survey
and tutorial articles, as well as reviews and commentary on topics
from these applications.
**** Instructions for submitting papers ***
Papers should be no more than 30 printed pages (approximately 15,000
words) with a 12-point font and 18-point spacing, including figures
and tables. Papers must not have appeared in, nor be under
consideration by other journals. Include a separate page specifying
the paper's title and providing the address of the contact author for
correspondence (including postal, telephone number, fax number, and
e-mail address). Send FOUR copies of each submission to the guest
editor listed below. Papers in ascii or postscript form may be
submitted electronically. Instructions for on-line submission are
given below.
==================================
Information For on-line submission
==================================
Kluwer Academic Publishers allows on-line submission
of scientific articles via ftp and e-mail. We will make
this system more user-friendly by incorporating it into our
KAPIS WWW server and use Netscape as the user-interface.
This is currently being prepared and will be implemented by
the end of this year. Below, please find the procedure that
should be used until then.
- an author sends an e-mail message to 'submit@wkap.nl'
containing the
following line
REQUEST SUBMISSIONFORM AIRE
AIRE = Artificial Intelligence Review (the 4-letter code that is used
at Kluwer)
- the author receives the electronic submission form (see attachment)
via e-mail with a dedicated file name filled in (and also the
information that is given at point 4: the journal's four-letter code plus
the full journal title)
- the author fills in the submission form and send it back to:
'submit@wkap.nl'
- at the same time, the author submits his/her article via anonymous ftp
at the following address: ftp.wkap.nl
in the subdirectory
INCOMING/SUBMIT, using the dedicated file name with an appropriate
extension
- at Kluwer, the article is registrated and taken into production in the
usual way
Papers Due: December 15, 1997
Acceptance Notification: March 1, 1998
Final Manuscript due: June 1, 1998
Guest Editor: Shivakumar Vaithyanathan, net.Mining, IBM Almaden Research Center,
650 Harry Road, San Jose, CA 95120
(408)927-2465 (Phone)
(408)927-2240 (Fax)
e-mail: shiv@almaden.ibm.com
Previous7NextTop
[The following is a commercial announcement. GPS]
Subject: MathSoft, Inc.
Date: Mon, 8 Sep 1997 20:07:04 -0400
From: Jason Mandell (jasonm@schwartz-pr.com)
MATHSOFT UNVEILS FAMILY
OF STATISTICAL DATA MINING PRODUCTS
Leading Developer of Data Analysis Software Highlights New Product
Line, Announces Strategic Alliance with Informix at DCI Data Warehouse
World
San Jose, Calif. April 7, 1997
MathSoft, Inc., (NASDAQ: MATH) a leading provider of advanced
calculation and analysis software, today introduced its family of
powerful statistical data mining products and announced a new
strategic partnership with Informix Software, Inc. The product line
addresses the growing need of corporate users for more effective tools
to analyze the data driving critical business and technical
decisions. MathSoft has laid the groundwork for further support of
corporate statistical data mining needs by joining the INFORMIX
DataBlade(R) Developers Program to develop the S-PLUS DataBlade(R)
module.
Success in today's data-intensive business environment hinges on the
ability to uncover trends and insights concealed in archived data and
to compare knowledge of historical events with current information,
creating predictive knowledge. The key to unearthing this type of
knowledge from corporate data is the analytical abilities of the
tools.
MathSoft's new product family is the first in the data mining market
to directly address the need for practical, effective analytics. The
product family is based on MathSoft's flagship data analysis tool,
S-PLUS(R), and MathSoft StatServer, a new product announced today
that distributes statistical analytics across the enterprise. The
product line will be further enhanced when MathSoft combines forces
with Informix's innovative database, providing custom-tailored
knowledge solutions that address complex business analysis
requirements.
'MathSoft is a recognized leader in data analysis technology,'
explained Charles Digate, president and CEO of MathSoft, Inc. 'Our
product line puts our analytical expertise to use in the important
arena of data mining and provides users with the type of tools they
need to analyze data interactively and reach more effective
conclusions. This new product line and partnership with Informix
underscores MathSoft's commitment to delivering integrated,
best-of-breed combinations of analytic and database solutions to our
customers.'
'The adaptability of Informix's and MathSoft's technology will allow
us to provide a seamless solution together,' said Bruce Golden, vice
president and general manager of Informix's data warehousing business
development unit. 'MathSoft is a recognized innovator of data analysis
tools, and we are excited to be working together to produce
statistical analysis products, the first of which will be earmarked
for the financial services industry.'
MATHSOFT'S STATISTICAL DATA MINING PRODUCT FAMILY
MathSoft's product family delivers a comprehensive set of data
analysis and statistical data mining products that are easy-to-use and
encourage professional users and knowledge workers at all
organizational levels to tap into the power of data contained in
corporate warehouses and data marts for more effective decision
making. The product line currently includes S-PLUS, a popular
statistical analysis package used by professionals in finance,
biomedicine and university research, and StatServer, a new product
announced today that distributes statistical analytics across the
enterprise to business executives and researchers at all levels. In
the future, it will include the next generation of S-PLUS, as well as
the S-PLUS DataBlade module, both of which will be available this
summer and will support MathSoft's goal to provide the most powerful,
easy-to-use tools for advanced data exploration and visualization.
DATABLADE TECHNOLOGY
A DataBlade module is a software component that extends the relational
database to manage new kinds of data. DataBlade modules add
domain-specific expertise and key functionality required for
user-defined data types such as points, lines, polygons,
etc. DataBlade modules plug-in directly to the database, making the
newly defined types and functions first-class citizens in the
database. Informix customers use a single DataBlade module or a number
of DataBlade modules simultaneously to create unique, integrated
information management solutions customized for their business
needs. Customers can choose from a growing portfolio of packaged
DataBlade modules from Informix and third parties, or define and
create their own with the DataBlade Developers Kit.
THE POWER OF S
All of MathSoft's data mining products are based on S, an
object-oriented language developed at Lucent Technologies (formerly
AT&T Bell Labs) specifically for data visualization and
exploration. MathSoft has exclusive worldwide rights to develop and
distribute products which incorporate the S technology.
Previous8NextTop
Date: Tue, 2 Sep 1997 16:41:16 +0200
From: Peter.Flach@kub.nl
(Peter A. Flach)
Subject: Visiting research fellowship in ILP at Bristol
Visiting research fellowship in Inductive Logic Programming
at the University of Bristol
The Department of Computer Science at the University of Bristol has a post
available for a visiting researcher with experience in Inductive Logic
Programming. The position is available from 1 October 1997 for a maximum of
15 months, and is supported by the ESPRIT Long Term Research project ILP2.
The main focus of the ILP2 work at Bristol is on descriptive induction of
non-classificatory rules; within the context of this work, the visiting
researcher is expected to contribute his or her particular approach.
More information on this position can be obtained from Peter Flach. Please
send your application and CV as soon as possible to Peter.Flach@cs.bris.ac.uk
.
Previous9NextTop
Date: Mon, 08 Sep 1997 17:39:11 -0700
From: Yuri Owechko (owechko@hrl.com)
Subject: Research position at Hughes Research Laboratories
RESEARCH OPPORTUNITIES IN SIGNAL AND IMAGE PROCESSING
AT HUGHES RESEARCH LABORATORIES
Hughes Research Laboratories (www.hrl.com) has an immediate opening for a
Research Staff Member to join a team of scientists in the Signal and Image
Processing Department. Team members in this department have developed
novel, state-of-the-art sensor fusion systems, neural networks,
time-frequency transforms, and image compression algorithms for use in both
commercial, and military applications.
The successful candidate will investigate advanced signal and image
processing techniques for information fusion, and pattern recognition
applications. Current work is focused on the application of information
fusion techniques, neural networks, and computer vision techniques for
automatic target recognition, automotive safety, and pattern recognition
applications. Specific duties will include theoretical analysis, algorithm
design, and software simulation.
Candidates are expected to have a Ph.D. in Electrical Engineering, Applied
Mathematics, or Computer Science. Strong analytical skills and
demonstrated ability to perform creative research, along with experience in
signal and image processing, information fusion, or pattern recognition are
required. Practical experience with Matlab, C, or C++ is essential. Good
communications and teamwork skills are keys to success. Based on
government restrictions regarding the export of technical data, a U.S.
citizenship or resident alien status is required.
Overlooking the Pacific Ocean and the coastal community of Malibu, the
Research Laboratories provides an ideal environment for you to make the
most of your scientific abilities. Our organization offers a competitive
salary and benefits package.
Additional information may be obtained from Lynn Ross. For immediate
consideration, send your resume to:
Lynn W. Ross
Department RM21
Hughes Research Laboratories
3011 Malibu Canyon Road
Malibu, CA 90265
FAX: (310) 317-5651
Internet: lross@msmail4.hac.com
Proof of legal right to work in the United States required. An Equal
Opportunity Employer.
Previous10NextTop
Date: Tue, 09 Sep 1997 17:38:53 +0100
From: ROSS DONALD KING (rdk@aber.ac.uk)
Subject: Univ. of Wales, Research Associate
URL:
Place: Department of Computer Science
University of Wales, Aberystwyth
Wales, UK
The Centre for Intelligent Systems seek a postdoctoral researcher to
help develop the successful protein secondary structure program DSC.
This program came second in the CASP2 international competition. The
ideal candidate will have a background in machine learning or
statistics and an interest in applying this to an important biological
problem. The research will be done in collaboration with the Imperial
Cancer Research Fund and Glaxo-Wellcome.
The appointment will be for a fixed term of three years on Grade 1A
(15,159 to 21,894 UK pounds).
Application forms, returnable by 24 October, and further particulars
from Staffing Office, Old College, King St., Aberystwyth, Ceredigion
SY23 2AX, Wales, UK. (tel. +44 1970-622055). Informal enquiries to
Ross D. King on +44 1970-622432 or rdk@aber.ac.uk.
See also
Virtual Gold Inc. Announces Data Mining Conference.
New York - Sept. 5, 1997. Virtual Gold Inc. and company founder
Dr. Inderpal Bhandari will host this year's most important
conference in the field of data mining. The conference is
entitled 'The Evolution of Data Mining: Technical Strategies
to Beat your Competition by the Year 2000'. The conference is
being held at the Millenium Hilton Hotel (New York, NY) over two days,
October 23 and 24, 1997. Featured speakers include leading
experts in the areas of data mining and warehousing,
high-performance computing, machine intelligence,
computer security and network computing. According to Dr.
Bhandari, data mining is quickly becoming a critical tool in
business. 'Those who can foresee the evolution of data mining
technology will gain a decisive and valuable competitive
advantage over their competition', notes Dr. Bhandari.
The invited guests embody a wealth of industrial knowledge and
experience that include such areas as finance, insurance,
telecommunications, entertainment, market research and the
government and defense sectors. In the upcoming conference,
data mining technologists and corporate technical strategists
are offered a unique forum at which to exchange and develop
ideas. 'This assembly has the technical and corporate
wherewithal to contribute to the shape of data mining in the
future - it's an exciting opportunity', says Dr. Bhandari.
Seats are limited. If you would like to be invited to this conference,
details can be found in www.virtualgold.com/conference.
Background
Inderpal Bhandari created IBM's Advanced Scout, a data mining
program used by teams of the National Basketball Association (NBA).
Advanced Scout allows teams to improve their performance by discovering
valuable hidden patterns in the game data and video. Dr. Bhandari is
an alumnus of IBM's prestigious Thomas J. Watson Research Center and is
a recipient of several IBM awards, including IBM's award for Outstanding
Innovation. He recently started Virtual Gold, Inc., a data mining company,
to enable businesses to capitalize on the technology of data mining. Previous12NextTop
Knowledge Discovery Nuggets Index