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Serafin Moral, UAI'98 Second Call for Papers, http://www.uai98.cbmi.upmc.edu
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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 Knowledge Discovery Mine site
at http://www.kdnuggets.com/
********************* Official disclaimer ***************************
All opinions expressed herein are those of the contributors and not
necessarily of their respective employers (or of KD Nuggets)
*********************************************************************
~~~~~~~~~~~~ Quotable Quote ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
If you can't find the truth where you are
where else do you think you will find it?'
The Buddha (thanks to gjamescleaning.com.au) Previous1NextTop
Date: Wed, 14 Jan 1998 00:02:53 -0800
From: Ronny Kohavi ronnyk@starry.engr.sgi.com
Subject: Leveraging Visual and Analytic Data Mining Guide from TechGuide
Reply-to: ronnyk@cthulhu.engr.sgi.com
TechGuide has a nice booklet on leveraging visual and analytic data
mining. They have used MineSet to show some examples.
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.
A few month part-time contract to become a full employment agreement
on February 1, 1998, should a match be identified.
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
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+++ Modern Regression and Classification: +++
+++ +++
+++ Widely applicable statistical methods +++
+++ for modeling and prediction +++
+++ +++
+++ Washington DC: April 6-7, 1998. +++
+++ +++
+++ Trevor Hastie, Stanford University +++
+++ Rob Tibshirani, University of Toronto +++
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
This two-day course will give a detailed overview of statistical models
for regression and classification. Known as machine-learning in
computer science and artificial intelligence, and pattern recognition
in engineering, this is a hot field with powerful applications in
finance, science and industry.
This course covers a wide range of models from linear regression
through various classes of more flexible models to fully nonparametric
regression models, both for the regression problem and for
classification.
Although a firm theoretical motivation will be presented, the emphasis
will be on practical applications and implementations. The course will
include many examples and case studies, and participants should leave
the course well-armed to tackle real problems with realistic tools. The
instructors are at the forefront in research in this area.
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Additional information is available at the Website:
************************************************************
Some quotes from past attendees:
'... the best presentation by professional statisticians I have
ever had the pleasure of attending'
'Superior to most courses in all aspects'
'I really liked how you emphasized concepts rather than
mathematical expressions'
'Your 2-day course has saved me months of research'
*************************************************************
The program stresses
practical implementation of data mining methods, tools, and techniques
for business intelligence applications. It features case studies by a
range of users, as well as technical discussions by many leaders in
the industry. Data visualization and integration with OLAP are also
key topics at this conference. We hope to see you there!
David Stodder
Conference Chair, Data Mining Summit
Editor-in-Chief, Database Programming & Design dstodder@mfi.com
Here's a submission for KDNUGGETS about a course I'll be teaching a few
months from now:
Lynd D. Bacon, Lynd Bacon & Assoc., Ltd. introduction to data mining and
knowledge discovery in market research,' American Marketing Association's
Applied Research Methods Conference, New Orleans LA 4/20-21/98. http://www.ama.org/conf/arm/
-lynd
/////////////////////////////\
| Lynd D. Bacon, Ph.D., President |
|~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~|
| LYND BACON & ASSOCIATES, LTD. http://www.lba.com
|
| marketing and management science mr.daemon@lba.com
|
| Homewood IL USA +1.708.957.0883 |
| --------------------- |
| Find out about the Chicago ASA monthly speaker series |
| at http://www.lba.com/asa-lunch.html
|
/////////////////////////////
Data Mining and Knowledge Discovery in Databases (KDD) have emerged from a
combination of many research areas: databases, statistics, machine learning,
automated scientific discovery, inductive logic programming, artificial
intelligence, visualization, decision science, and high performance
computing.
While each of these areas can contribute in specific ways, KDD focuses on
the value that is added by creative combination of the contributing
areas. The goal of PKDD'98 is to provide a European-based forum for
interaction among all theoreticians and practitioners interested in data
mining. Interdisciplinary collaboration is one desired outcome, but the main
long-term focus is on theoretical principles for the emerging discipline of
KDD, especially on KDD-specific principles that go beyond each contributing
area.
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All papers accepted for regular and poster presentations will be published
in the conference proceedings.
PROGRAM CO-CHAIRS:
Jan Zytkow Mohamed Quafafou zytkow@uncc.eduquafafou@irin.univ-nantes.fr
Dept. of Computer Science IRIN, 2 rue la Houssiniere
UNC Charlotte BP 92208 - 44322 Nantes cedex 03
Charlotte, NC 28223 France
USA
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IMPORTANT DATES:
Papers submission deadline: May 15th, 1998
Notification of acceptance: June 15th, 1998
Camera ready papers: July 5th, 1998
PANEL DISCUSSIONS: Proposals are sought for panels that stimulate
interaction between the communities contributing to KDD. Include title, the
main goals, prospective participants and a summary of the topics to be
discussed. Submission to zytkow@uncc.edu
by May 15th, 1998. Notification of
acceptance by June 5th, 1998.
TUTORIALS: Proposals are solicited for tutorials that: (1) transfer know-how
and provide hands-on experience, (2) combine two or more areas (e.g. rough
sets and statistics, high-performance computing and databases, etc), or (3)
cover application domains such as finance, medicine, or automatic control.
Submission to zytkow@uncc.edu
by May 15th, 1998. Notification of acceptance
by June 5th, 1998.
DEMONSTRATIONS OF SOFTWARE: Demonstrations of software for data mining and
knowledge discovery are invited, including both commercial and
experimental systems. Send descriptions to quafafou@irin.univ-nantes.fr
by
July 15th, 1998.
1st INTERNATIONAL CONFERENCE ON
ROUGH SETS AND CURRENT TRENDS IN COMPUTING (RSCTC'98)
June 22 - 26 1998, Warsaw, Poland
CALL FOR PARTICIPATION
The conference is devoted to the following topics :
rough set theory and applications, fuzzy set theory and applications, knowledge
discovery and data mining, decision support systems, machine learning,
evolutionary algorithms, neural networks, computing with words and
granular computing, molecular computing, grammar systems, Petri nets
and concurrency, complexity aspects of soft computing, pattern
recognition and image processing, statistical inference, multi - agent
systems, logical aspects of soft computing, applications of soft
computing techniques in robotics, medicine, virtual reality
and its aim is to bring together eminent experts in diverse fields of
expertise in the area of Soft Computing and Applications in order to
facilitate mutual understanding and cooperation and to help in
cooperative work aimed at new hybrid paradigms possibly better suited
to various aspects of analysis of real life phenomena.
We plan to carry the conference out in parallel sessions dedicated to the above
topics as well as to have plenary sessions.
Honorary chairs Edward Feigenbaum (USA), Zdzislaw Pawlak (Poland),
Carl Petri (Germany), Lotfi Zadeh (USA)
Conference site / Hotel
The Barnabite Conference Center ; Smoluchowskiego 1 ; 02 679 Warsaw
The First International Conference on Discovery Science
Aqua Plaza, Hotel Uminonakamichi, Fukuoka, Japan
December 14-16, 1998
The first international conference on Discovery Science (DS '98) will
be held at Hotel Uminonakamich, Fukuoka, Japan during December 14 to
16, 1998. The conference will be sponsored by Grant-in-Aid for
Scientific Research on Priority Area 'Discovery Science' in
cooperation with SIG of Data Mining, Japan Society for Software
Science and Technology.
The 'Discovery Science' is a three year project from 1998 to 2000 that
targets to (1) develop new methods for knowledge discovery, (2)
install network environments for knowledge discovery, and (3)
establish the Discovery Science as a new area of Computer Science. A
systematic research is planned that ranges over philosophy, logic,
reasoning, computational learning and system developments.
The main objective of this conference is to provide an open forum for
intensive discussions and interchange of new information, be it
academic or business, among researchers working in the new area of
Discovery Science.
Topics of interest within the scope of this conference include, but
not limited to, the following areas: Logic for/of knowledge discovery,
knowledge discovery by inferences, knowledge discovery by learning
algorithms, knowledge discovery by heuristic search, scientific
discovery, knowledge discovery in databases, data mining, knowledge
discovery in network environments, inductive logic programming,
abductive reasoning, machine learning, constructive programming as
discovery, intelligent network agents, knowledge discovery from
unstructured and multimedia data, statistical methods for knowledge
discovery, data and knowledge visualization, knowledge discovery and
human interaction, and human factors in knowledge discovery.
Invited lectures will be delivered by Dr. Pat Langley (Inst. for the
Study of Learning & Expertise), Prof. Stephen Muggleton (University of
York), Prof. Heikki Mannila (University of Helsinki) , Prof.
Shinichi Morishita (University of Tokyo) and Prof. Keiichi Noe (Tohoku
University).
<>
Call for Posters and Demos
DS'98 also invites posters and software demonstrations as an
important part of the conference. For poster and demo, send a
two-page abstract (in the same style of the ordinary papers) by
email to ds98@i.kyushu-u.ac.jp
by July 26, 1998. After a
reviewing process by PC committee, the accepted abstracts will
be included in the proceedings. For software demonstrations, a
limited number of computer equipments will be available. Please
contact to Ayumi Shinohara (ayumi@i.kyushu-u.ac.jp).
Call for Papers
High Performance Data Mining
Tuesday March 31, 1998
Orlando, Florida
Held in conjunction with
12th International Parallel Processing Symposium (IPPS)
9th Symposium on Parallel and Distributed Processing (SPDP)
The last decade has seen an explosive growth in database technology
and the amount of data collected. Advances in data collection, use of
bar codes in commercial outlets, and the computerization of business
transactions have flooded us with lots of data. We have an unprecedented
opportunity to analyze this data to extract more intelligent and useful
information. Data mining is the efficient supervised or unsupervised
discovery of interesting, useful, and previously unknown patterns from
this data. Due to the huge size of data and amount of computation
involved in data mining, parallel processing is an essential component
for any successful large-scale data mining application. This workshop
will provide a forum for presentation of recent results in parallel
computation for data mining including applications, algorithms, software,
and systems.
Previous10NextTop
Date: Wed, 14 Jan 1998 22:05:16 +0000
From: Serafin Moral smc@decsai.ugr.es
Subject: UAI'98 Second Call for Papers
NEW UPDATED INFORMATION ABOUT UAI-98 CONFERENCE
>>>> New revised deadline to receive full papers.
>> Abstract and paper submission data received by: Monday, February 23, 1998
>> Postscript files of the papers received by: Thursday, February 26, 1988
>>>> Length of submitted papers has been clarified.
For more details about the updates given below, please visit the
UAI-98 WWW page at
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