(text)
Andreas Weigend, Computational Finance Jan 6-8 1999 at
NYU/Stern: CFP and Registration http://www.stern.nyu.edu/CF99
--
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~~~~~~~~~~~~ Quotable Quote ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
When one knows a number of things, and understands how they are
categorized, then he has a great advantage over one who has the same
knowledge without such distinction. It is .. like the difference between
looking at well-arranged garden, planted in rows .., and seeing ...
forest growing in confusion.
Moshe Chaim Luzzatto, intoduction to 'The Ways of God', c. 1740-s,
(thanks to Simon Streltsov simon@alphatech.com)
Previous1NextTop
Date: Wed, 05 Aug 1998 16:57:34 -0500
From: Won Kim won.kim@cyberdb.com
Subject: SIGKDD is officially chartered
Web: www.acm.org/sigkdd
ACM has just notified me today that the SIG Board has voted to
officially charter SIGKDD.
We are now an ACM SIG. Amen.
(more information on SIGKDD and its planned activities
will be announced at KDD-98 in New York City. GPS)
Previous2NextTop
Date: Tue, 18 Aug 1998 16:46:21 -0400
From: iparsa@epsilon.com
(Ismail Parsa)
Subject: Exciting Data Mining Forum in Manhattan, August 28-29, 1998
Web:
Dear Tri-State (NY, CT, NJ and even Philadelphia) area Data Miners,
Statisticians, Programmer/Analysts and Students:
It is my pleasure to invite you to join the Exhibit session of the
4th International Conference on Knowledge Discovery and Data Mining
(KDD-98). This exhibit is *FREE OF CHARGE*.
The KDD-98 Exhibit program will feature demonstrations by 18 data
mining tools/vendors, 13 research prototypes and 5 publishers. There
will also be 3 exhibit presentations. Refreshments will be served.
The Exhibit session speakers are:
o Gordon Linoff, co-author of _Data Mining Techniques_, will
present 'Data Mining in the Real World'
o Shivakumar Vaithaynathan will present 'Data Mining on the
Internet: Overview, Algorithmic Challenges and Applications'
o Ismail Parsa will present 'Data Mining Tools'
A select list of exhibitors includes:
o ISL Decision Systems, Clementine
o Isoft, Alice
o Megaputer Intelligence, PolyAnalyst
o Salford Systems, CART
o SAS Institute, Enterprise Miner
o Sentient Machine Research, DataDetective
o SGI, MineSet
o SRA International, KDD Explorer
o Thinking Machines, Darwin
o Unica Technologies, PRW & Model1
o Urban Science, GainSmarts
o WizSoft, WizWhy & WizRule.
For a complete list of the exhibitors please refer to:
+--------------------------------------------------------------------+
| Location, Important Dates & Exhibits Schedule |
+--------------------------------------------------------------------+
The Conference will be held in midtown Manhattan in New York City, at
the New York Marriott Marquis Hotel between August 27-31, 1998. For
more information about the conference, please visit URL:
Data Mining in the Real World. This presentation will discuss the
issues of data mining in the real world. It will touch on the
relationship of data mining with a data warehouse (is it really
easier?) and on issues related to managing data and choosing
particular techniques.
Data Mining On the Internet: Overview, Algorithmic Challenges and
Applications. The advent of the World Wide Web has caused a
dramatic increase in the 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. In this talk, I will provide
examples of applications where data mining could be applied and
then focus on the algorithmic challenges along. I will also
discuss some new algorithms and provide some results.
Data Mining Tools. The data mining tools marketplace is diverse.
There are tools that offer broad-based data mining capability,
tools aimed at solving the problems of a particular industry,
tools combined with a service offering, black-box tools and
vendors/tools offering custom solutions such as CRM, campaign
management, etc.
We will first segment the data mining tools marketplace. We will
then learn how to differentiate between the many data mining tools
for the best return on investment. We will finally review the
summary results of a real-life data mining tool evaluation case
study. Come see what all the hype is all about!
KDD-98 is the premiere event for the data mining community, bringing
together researchers, practitioners and application developers from
different KDD related fields such as machine learning, statistics,
databases, data visualization, database marketing and finance to
share ideas/experiences, and to explore new concepts, applications,
tools and techniques. For more information about the conference,
please visit URL: www.kdnuggets.com/meetings/kdd98
Come confer with us in the midst of technical discussions, demos,
exhibits and refreshments.
If you plan to attend, please R.S.V.P iparsa@epsilon.com
so we can
plan accordingly.
Previous3NextTop
Date: Thu, 13 Aug 1998 01:43:26 -0400
From: iparsa@epsilon.com
(Ismail Parsa)
Subject: KDD-CUP: List of Participants
Web: kdnuggets.com/meetings/kdd98/kdd-cup-98.html
KDD-CUP is a knowledge discovery and data mining tools competition
held in conjunction with the International Conference on Knowledge
Discovery and Data Mining (KDD-98.) For more information about the
CUP, please visit the web site at
Last year, the CUP enjoyed worldwide participation of 45 data mining
tools. This year, it is enjoying worldwide participation of 57
contestants. 18 of the 57 participants have elected to stay
anonymous. The software status of those that elected anonymity is as
follows:
4 Commercial
4 Freeware
10 Research Prototype.
The following 39 participants wish to be identified.
APN (Adaptive Probabilistic Networks) Berkeley/SRI/Stanford
BAYDA/PRO Complex Systems Computation Group
(CoSCo), University of Helsinki
BNB (Boosted Naive Bayes Classifier) University of California San Diego
BPSOM Eindhoven University of Technology
CARRL Austrian Research Institute for AI
DataBase Mining Marksman HNC Software Inc.
DataDetective Sentient Machine Research
DataLamp University of East Anglia
Discovery Board Rutgers University
DMZ Yongwon Lee, Lockheed Martin ATC
(tool not affiliated with Lockheed
Martin ATC.)
DTI v5.0 ECCI-University of Costa Rica
Enterprise Miner SAS Institute
Fragment-Potential QueryObject Systems, NY &
Institute for Information
Transmission Problems, Moscow
GainSmarts Urban Science Applications, Inc.
ICL Katholieke Universiteit Leuven
IGLUE CRIL
Information Network Tel Aviv University
JABC University of Constance, Germany
JAM Florida Institute of Technology &
Columbia Univeristy
JAWS University of Waikato, New Zealand
Kepler Dialogis Software & Services GmbH
KnowledgeMiner Frank Lemke, Script Software
KnowMan DataMiner(research version) Intellix / Riso National Laboratory
LPDT Rensselaer Polytechnic Institute
MineSet Silicon Graphics, Inc.
Mixtures of Trees Massachusetts Institute of Technolog
Model 1 Unica Technologies, Inc.
ModelQuest Enterprise AbTech Corp.
Otis Randy Kerber, NCR (tool not affiliat
with NCR)
PolyAnalyst Megaputer Intelligence Ltd.
QS Iona Corp.
Rdt/Db Informatik LS VIII, Universitaet Dortmund
SENN Sales Siemens Nixdorf Business Service
The Shrunken-Belly Method Edward Malthouse, Northwestern University
TILDE Katholieke Universiteit Leuven
Tutti 0.1 Tampere University of Technology
WARMR Katholieke Universiteit Leuven
WhiteCross HeatSeeker MRJ Technology Solutions/WhiteCross
WizWhy WizSoft
+--------------------------------------------------------------------+
| KDD-CUP-98 Program Committee |
+--------------------------------------------------------------------+
o Vasant Dhar, New York University, New York, NY
o Tom Fawcett, Bell Atlantic, New York, NY
o Georges Grinstein, University of Massachusetts, Lowell, MA
o Ismail Parsa, Epsilon, Burlington, MA
o Gregory Piatetsky-Shapiro, Knowledge Stream Partners, Boston, MA
o Foster Provost, Bell Atlantic, New York, NY
o Kyusoek Shim, Bell Laboratories, Murray Hill, NJ
+--------------------------------------------------------------------+
| KDD-CUP PROCESS & IMPORTANT DATES (UPDATED) |
+--------------------------------------------------------------------+
o Registration and signing of the NDA (Non-Disclosure Agreement)
July 1-15, 1998
o Release of the datasets, related documentation and the KDD-CUP
questionnaire
July 22, 1998
o Return of the results and the KDD-CUP questionnaire
August 19, 1998
o KDD-CUP Committee evaluation of the results
August 19-25
o Individual performance evaluations send to the participants
August 26, 1998
o Public announcement of the winners and awards presentation during
KDD-98 in New York City
August 29, 1998
I work for the Hungarian Government in the
Finance Ministry. One of my work is to build up the budget data warehouse
from Treasury database and other sources. Can you help me find some papers
on budget related data mining, or so?
Journal of Computational Intelligence in Finance
Final Call for Papers
Special Issue on
'Financial News Analysis using Distributed Data Mining'
The Journal of Computational Intelligence in Finance, a peer-reviewed
technical journal, published by Finance & Technology Publishing, is
seeking papers for review and publication on 'Financial News Analysis
using Distributed Data Mining'.
The Journal of Computational Intelligence in Finance publishes applied
research and practical applications of high quality that are based on
sound theoretical, empirical or quantitative analysis. Covers the
application of advanced computational technologies and analytical
techniques for financial modeling, investing and trading, and risk
management, for practitioners and applied researchers.
Papers published in JCIF are eligible for the 'Distinguished Essay on
Computational Intelligence in Finance' award, which is selected by the
Editorial Board each year.
SPECIAL TOPIC: Financial News Analysis using Distributed Data Mining
PAPERS DUE: September 15, 1998
ACCEPTANCE NOTIFICATION: November 30, 1998
FINAL REVISED MANUSCRIPTS DUE: January 15, 1999
PUBLICATION DATE: March 1999
GUEST EDITORS
Zoran Obradovic Stuart H. Rubin
Associate Professor Associate Professor
Elec. Eng. & Comp. Sci. Dept. of Comp. Sci.
Washington State University Central Michigan University
Pullman, WA 99164-2752, USA Mt. Pleasant, MI 48859, USA zoran@eecs.wsu.edurubin@cps.cmich.edu
MOTIVATION
Recent technological developments, the rapid growth of the World Wide Web,
and maturing corporate intranet structures have led to the rapid
dissemination of huge amounts of financial news and information (newspaper
articles, financial services information, corporate publications, stock
exchange news, peer-reviewed financial journal articles, etc.). However,
cost and time constraints prohibit an exhaustive search through or download
of all potentially relevant financial news and information available on the
Internet, for later analysis and processing. One possible solution is to
distribute information sampling over a large number of locations in order
to classify local data, construct a pool of relevant information, and
generate useful rules that might be further analyzed or processed at a
central location. This requires intelligent and dynamic domain
decomposition, as well as flexible software agents for symbolic information
processing.
For details on ABSTRACTS and PAPER submission requirements, and
additional details, see:
The slides to my invited talk at the international conference
on machine learning (ICML-98),
Crossing the Chasm: From Academic Machine Learning to
Commercial Data Mining
You have strong analytical skills with a background in statistical
analysis and statistical techniques such as regression analysis,
clustering, ANOVA. You are self motivated and thrive working in a team
environment. You have excellent relationship building skills and
collaboration skills which allow you to manage vendor and supplier
relationships, as well as work the marketing team to create a better
understanding of customer needs.
Day-to Day Role:
As a member of the Business Communications team you will:
- Facilitate the use of customer understanding (segmentation,
models and queries) on project teams related to the development and
marketing of new products and services including determination of
target markets, market research and generating customer lists for
campaign purposes.
- Develop and refine segmentation models to assist business and marketing
strategies
- Develop predictive and propensity models to assist in the targeting of
new and existing products and services
- Support the product advisors and other users of the marketing database in
queries and reporting
- Work with the Marketing Database Administrator to ensure the database
continues to evolve to meet the needs of the SMA
- Support other Analysts in the area of understanding market trends,
competitors and business unit performance
MT&T is a leader in knowledge based marketing and this position
offers tremendous learning opportunity. You will be in on the ground
floor of this exciting new way of understanding our customers. MT&T
continually supports employees in their continuing development and
education through the creation and implementation of a personal
development plan.
Must Have Skills:
- Analytical skills with background in statistical analysis and statistical
techniques
- Database querying capability, e.g. experience writing queries
- Project Management skills
- Strong written and communications skills
- Relationship building and collaboration skills
- Excellent organizational and coordination skills
Nice to Have Skills
- MBA specializing in Econometrics/Statistics or Masters of Applied Science
Primary Location of this position: 250 Brownlow Ave., Dartmouth, Nova Scotia
Job Title: Information Technology Engineer Consultant
Location: Roseville, CA
Essential Responsibilities:
Provide technical leadership and management skills in worldwide
project development. Analyze customer marketing and process needs, and
translate them into technical requirements. As a
knowledge engineering expert on a team with members who have expertise
in other functional areas,
identify/evaluate/recommend knowledge-based approaches to meeting those
requirements. Model/design/simulate proposed
approaches into a system solution that is consistent with existing and
future technical architecture and support environment.
Manage the technical relationship with project partners including
consulting/contract/offshore people and ensure project
development activities to follow the methodology of established project
development life cycle.
Musts:
Bachelor's Degree in CS. Strong knowledge and two-year project
experience working in AI and knowledge-based systems.
At least two years experience working on NT & UNIX platforms, C/C++
languages. At least one year experience developing
database applications (e.g., Oracle, Sybase). At least one-year
experience developing software through all phases of the
development life cycle.
Desired:
MSCS or equivalent or higher. Experience with case based reasoning,
Baysian belief networks, knowledge-based reasoning
with uncertainty. Experience with OOA/OOM, Java programming,
client/server architecture, component-and agent-based
enterprise solutions design.
If interested, please forward all resumes to Paul Farmer at Hewlett
Packard (paul_farmer@hp.com).
Previous10NextTop
Date: Tue, 18 Aug 1998 12:01:13 -0400
From: Aviva Lev-Ari Aviva.Lev-Ari@Time-0.com
Subject: Employment Opportunity for an MSc or Ph.D. level
Web:
Industry has strond demand for applied recent graduates in
quantitative disciplines
I would like to explore the possibility of interviewing few of the
graduate students in the Stat/Math/OR/CS/Econometrics department.
Respectively, please ask the secretary of the Career Placement Center
to post an Ad, or e-mail to all graduate students in the above
departments, the following Job description.
Employment opportunity for a Stat/Math/OR/CS/Econ MSc or Ph.D. level.
Applied Research in Internet Economics and Electronic Commerce
Transaction Information Analytics and Data Mining
Profile:
Extremely bright, creative and inquisitive young broadly trained in
Quantitative Methods and Measurement Theory with an undergrade
education in Stat/Math/OR/CS/Econometrics/Psychometrics.
Modifyable into an independent applied researcher and heavy user of
S-Plus, SAS, Mathematica, MatLab, LaTex and graphical software.
Excellent writing (technical editorial skills) and oral communication
skills (ability to explain technical terms to non-technical
professionals). Independent in exploration of newly research concepts
assigned to, offer creative ideas to the project, and amenable to be
mentored and expand his/hers knowledge boundaries on a daily basis.
A team player, substantiated professional confidence, highest
integrity with handling data, choosing methods and respecting the
technical savvy of other peers and management.
Compensation:
Master Level: up to $45K - $60K
Ph.D. Level: up to $60K - $80K
Contact:
Aviva Lev-Ari, Ph.D.
Director of Information Analytics
Perot Systems Corp
101 Main St.
Cambridge, MA 02142
(617) 303-5011
The next Silicon Graphics' Data Mining with MineSet course
will be held in Silver Springs, MD Sept 8-10.
The course after will be Oct 20-22 in Dallas, TX.
By attending the course, you will understand:
o What is the knowledge discovery process.
o What are the capabilities and limitations of the MineSet product.
o How to use MineSet to solve your business problems and
maximize the value of your data.
o How to effectively manage your mineset sessions.
o How to connect to your existing databases and take advantage of
parallel hardware.
o How to use the MineSet interfaces to build applications.
o How to deploy models across your company, how to launch
visualizations from the web, and how to setup PCs to connect to
MineSet.
The three-day course is taught by an outside instructor who
regularly consults in data mining and can share a balanced perspective
of the strengths and weaknesses of MineSet.
The classroom is set up with Silicon Graphics workstations to
facilitate hands-on training with one person per machine. The classes
are small (about 10 people). The class costs $1500.
Previous12NextTop
Date: Tue, 4 Aug 1998 03:14:22 -0400 (EDT)
From: Jan M Zytkow, zytkow@uncc.edu
Subject: Summary of Upcoming Knowledge Discovery Meetings
Web: www.kdnuggets.com/meetings
Good news for all interested in automation of discovery !!!
Please forward to your colleagues !!!
In 1998 and 1999 we are going to have a large number of conferences on
knowledge discovery organized in different parts of the world. You
may not be aware of some of them. There is still time to register for
each conference and to submit papers to most of them. For your
convenience, this is a summary of TEN conferences:
October 23-28, 1998, Research Triangle Park, NC, USA
6th International Workshop on Rough Sets (knowledge discovery
is the main focus)
For more information email: anita@cs.sunysb.edu
November 23, 1998, Singapore
Workshop on Knowledge Discovery and Data Mining
at 5th Pacific Rim International Conf. on AI
See http://www.iscs.nus.edu.sg/~liub/pricaiwp.html
PAPERS SUBMISSION DEADLINE: AUGUST 25
December 17-19, 1998, Pavia, Italy
Conference on model-based reasoning in scientific discovery
For more info: http://philos.unipv.it/courses/progra1.html
ABSTRACT SUBMISSION DEADLINE: JULY 31.
April 5-9, 1999, Orlando, FL, 1999
SPIE Conference on Data Mining and Knowledge Discovery http://members.tripod.com/~belur/kdd.html
DEADLINE FOR ABSTRACTS SUBMISSION: AUG. 24, 1998
April 26-28, 1999, Beijing, China
PAKDD-99 = The Third Pacific-Asia Conference on
Knowledge Discovery and Data Mining http://ain2.ai.csse.yamaguchi-u.ac.jp/pakdd99
PAPERS DUE: OCTOBER 10, 1998
August 9-11, 1999, Amsterdam, The Netherlands
IDA-99: Third Symposium on Intelligent Data Analysis http://www.wi.leidenuniv.nl/~ida99
PAPERS DUE: FEBRUARY 1, 1999
=====================================================================
[ ] I would like to attend the CRISP-DM SIG workshop in New
York on 1st September 1998
[ ] I am already a CRISP-DM SIG member.
[ ] I am not currently a CRISP-SIG member, but would like to join.
[ ] I would be willing to give a presentation on my data mining
experiences and requirements for a data mining process model
[ ] I would be willing to present my comments on the current draft
process model
[ ] I am happy for workshop participants to receive a copy of my
presentation(s)
Name :
Organisation :
Postal Address:
Email :
=====================================================================
Schedule: September, 1st, 1998, 10.00 - 17.00
---------------------------------------------------------------------
VENUE NCR New York
1290 Avenue of the Americas
New York, NY
USA
DIRECTIONS: NCR New York is located at 1290 Avenue of the Americas,
New York, NY on the corner of 51st and 6th Avenue. The NCR office is on the
fifth floor of this building.
Note, NCR New York is only five blocks from the KDD '98 venue, the
Marriot Marquis Hotel.
=====================================================================
C R I S P - D M S I G W O R K S H O P
T E N T A T I V E A G E N D A
=====================================================================
THE CRISP-DM PROJECT
10.00 - 10.15 Jens H. Hejlesen NCR
THE CURRENT CRISP-DM PROCESS MODEL
10.15 - 11.00 Thomas Reinartz Daimler-Benz
WHY DO TOOL VENDORS NEED A TOOL-INDEPENDENT PROCESS MODEL?
11.00 - 11.30 Colin Shearer ISL
11.30 - 12.00 Randy Kerber NCR
---------------------------------------------------------------------
12.00 - 13.00 LUNCH
---------------------------------------------------------------------
SIG PARTICIPANTS PRESENTATIONS
13.00 - 13.15 David Jensen Univ. of Massachusetts
13.15 - 13.30 Ronny Kohavi Silicon Graphics
13.30 - 13.45 Michael Muratet Infotec
13.45 - 14.00 Dan Steinberg Salford Systems
14.00 - 14.15 Jaap Verhees ELC Object Technologie B.V.
14.15 - 14.30 Chris Westphal Consultant
14.30 - 14.45 Graham Williams CSIRO Mathematical and Inf. Sc.
14.45 - 15.00 NN NN
---------------------------------------------------------------------
15.00 - 15.30 COFFEE BREAK
---------------------------------------------------------------------
CONCLUSIONS
15.30 - 16.30 Discussion
16.30 - 17.00 Summary and Next Steps
=====================================================================
For more information contact crisp@dbag.ulm.daimlerbenz.com http://www.ncr.dk/CRISP
Prof. Nelson F. F. Ebecken
COPPE/Federal University of Rio de Janeiro
Caixa Postal 68506
21945-970 Rio de Janeiro - RJ
Brazil
Fone: (55 21) 560.8993/560.8776/560.7941
Fax: (55 21) 280.9545/290.6626
e-mail: nelson@ntt.ufrj.br
5th Pacific Rim International Conference on Artificial Intelligence
Nov 22-27 1998, Singapore
Introduction
Knowledge discovery and data mining (KDD) has become an active and
growing research area. It is not only of academic interest, but also of
great practical significance. It has attracted a large number of researchers
and practitioners from many disciplines, e.g., machine learning, databases,
AI, statistics, and data visualization. The reason for this tremendous
interest in KDD is obvious. Due to the rapid computerization of the past
two decades, almost all organizations and companies have collected a huge
amount of data in their databases. These organizations and companies need
to understand their data and/or to discover useful knowledge from the data
that can be used for a competitive advantage. KDD aims to help them to do
just that.
This workshop aim to bring together researchers and practitioners from
various disciplines concerned with mining or discovering useful knowledge
from data. The objective of this meeting is to discuss the following issues:
What are the major challenges in data mining applications?
What are promising research directions in solving these challenging problems?
What are the most promising directions for cross-disciplinary research?
--> Aug 31, 1998: Deadline for submissions
--> Oct 31, 1998: Program posted on the web
--> Dec 1, 1998: Deadline for early registration
The sixth international conference Computational Finance (CF99) will
be held at NYU's Leonard N. Stern School of Business, sponsored by the
New York University Salomon Center, the Center for Research on Information
Systems and the Department of Statistics and Operations Research.
Computational Finance has emerged as a genuinely cross-disciplinary
research meeting. CF99 is the sixth in a series of conferences that
have been sponsored by the California Institute of Technology and the
London Business School. In the past, this conference was called Neural
Networks in the Capital Markets (NNCM). The expanding set of computational
tools has moved this meeting from its original emphasis on neural
network techniques to a broad spectrum of different methodologies.
With several hundred attendees, this fully refereed conference has
become an international forum where original research in advanced
computational applications in finance is presented and discussed.
CF99 brings together decision-makers and strategists from the
financial industries, with academics from finance, statistics,
economics, information systems and other disciplines. In the last
few years, the conference has seen papers covering many different
computational techniques including: statistical machine learning, Monte
Carlo simulation, data mining, knowledge discovery, bootstrapping,
genetic algorithms, nonparametric methods and information theory.
Applications in many different areas are welcome, including but not
limited to: risk management, asset allocation, dynamic trading and
hedging strategies, forecasting, numerical solutions of derivative PDEs,
option pricing and trading cost control. Studies may cover any major
international financial market including equity, foreign exchange,
bond, commodity and derivatives. The conference emphasizes in-depth
analysis and comparative evaluation with established approaches.
CF99 begins with a full day of tutorials designed to inform the
diverse group of participants on a selection of the latest tools
and research results. The tutorial speakers (on January 6) are:
o Prof. Stephen Figlewski, Stern School of Business, New York University
o Prof. David A. Hsieh, Fuqua School of Business, Duke University
o Prof. Benjamin van Roy, Stanford University
o Prof. Halbert White, University of California, San Diego.
CF99 has two distinguished keynote speakers (on January 7 and 8):
o H. Gifford Fong, President of Gifford Fong Associates
o David E. Shaw, PhD, Chairman and CEO of D. E. Shaw & Co., Inc.
CF99 also features several invited speakers sharing their expertise
from both the academic and applied perspectives, as well as talk and
poster sessions for the accepted papers. A selection of these papers
will appear in a book published by Kluwer in summer 1999.
Knowledge Discovery Nuggets Index