--
Data Mining and Knowledge Discovery in Databases (KDD)
community, focusing on the latest research and applications.
Contributions are most welcome and should be emailed,
with a DESCRIPTIVE subject line (and a URL, when available) to (kdd@gte.com).
E-mail add/delete requests to (kdd-request@gte.com).
Nuggets frequency is approximately weekly.
Back issues of Nuggets, a catalog of S*i*ftware (data mining tools),
and a wealth of other information on Data Mining and Knowledge Discovery
is available at Knowledge Discovery Mine site, URL http://info.gte.com/~kdd.
-- Gregory Piatetsky-Shapiro (moderator)
********************* Official disclaimer ***********************************
* All opinions expressed herein are those of the writers (or the moderator) *
* and not necessarily of their respective employers (or GTE Laboratories) *
*****************************************************************************
~~~~~~~~~~~~ Quotable Quote ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
'This is far more difficult than finding needles in a haystack,'
astronomer Julia Kennefick, describing search for quasars in the huge
databases of space observations. Previous1NextTop
>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Return-Path: (fayyad@aig.jpl.nasa.gov)
Date: Fri, 29 Dec 95 10:03:59 PST
From: fayyad@aig.jpl.nasa.gov
(Usama Fayyad)
To: gps@gte.com
Subject: item for Nuggets
Gregory:
please post this press release to KDD nuggets. I did post
an item about it a few months back when we got the initial
results. This is the official news release put out by Caltech,
JPL, and Ohio State Univ. simultaneously about 2 weeks ago.
this is an item to go under 'Data Mining at large in the Cosmos'
:-)
Thanks,
Usama.
=====================================================================
News Release
California Institute of Technology
Office of Media Relations
Pasadena, CA 91106
(818) 395-3227
For Immediate Release December 1, 1995
Astronomers Announce Discovery of Extremely Distant Quasars
PASADENA--Astronomers have discovered 16 new extremely distant
quasars, the result of a search made nearly 40 times more efficient than
previously possible by applying artificial intelligence to the new Palomar
digital sky survey. This novel technique allows researchers to study more
easily the formation of quasars and large-scale structures in the early
universe.
'This is one of the first successful major applications of artificial
intelligence techniques in astronomy and space science,' said Usama
Fayyad, a scientist at the Jet Propulsion Laboratory (JPL) in Pasadena,
California. 'Data mining techniques and automated data analysis are
becoming a necessity in this new era of astronomy and space science where
instruments can generate tremendous amounts of data. The discovery of
these new quasars shows how efficiently scientists can explore vast
databases such as the Palomar sky survey, using this novel data-mining
technology. And this technique is applicable to many other data-rich
fields. It is a truly new way of doing science.'
These results are reported in the December issue of the Astronomical
Journal in a paper by Julia Kennefick, a postdoctoral researcher at Ohio
State University; S. George Djorgovski, an assistant professor of
astronomy at Caltech; and Reinaldo Ramos de Carvalho, a senior research
fellow in astronomy, also at Caltech. Kennefick is a former graduate
student of Djorgovski. Some of the technical developments leading to
these discoveries have been reported earlier by Djorgovski, Fayyad, and
their colleagues.
The astronomers have found 16 new quasars at redshifts greater than 4
(redshift is a measure of distance in cosmology), corresponding to
look-back times in excess of 90 percent of the age of the universe. Such
objects are exceedingly rare, and finding even a few of them is considered
very important by astronomers. The recently discovered quasars are
providing a new glimpse of the very early universe.
'We see these quasars at a time when the universe was only a billion
years old, when the first structures were just forming,' explained
Djorgovski. The study in the Astronomical Journal confirms a previous
suggestion that the number of quasars diminishes rapidly as one looks back
toward earlier epochs in the universe. In other words, astronomers are
seeing the appearance of the first quasars, when the universe was only
one-tenth of its present age, or possibly even younger.
The scientists, led by Djorgovski, are conducting a systematic search
to discover large numbers of extremely distant quasars using a set of
sophisticated artificial intelligence (AI) software tools developed for
this task in collaboration with Fayyad and his Machine Learning Systems
Group at JPL.
The astronomers are applying these AI tools to a new digital survey
of the entire northern sky. The digital sky survey is being produced as a
collaborative project between Caltech and the Space Telescope Science
Institute in Baltimore, Maryland, and is based on the photographic sky
survey done with the 48-inch Oschin Telescope, a Schmidt telescope at
Caltech's Palomar Observatory in northern San Diego County. When
complete, the digital sky survey will contain enough information to fill
about 6 million books and will include about 2 billion stars, galaxies,
quasars, and other objects.
In order to efficiently process this unprecedented amount of
astronomical information, a team of scientists from JPL led by Fayyad, in
collaboration with Djorgovski and his former student Nicholas Weir, now at
Goldman, Sachs and Company in New York, developed a powerful software
system, called the Sky Image Cataloging and Analysis Tool (SKICAT). The
SKICAT system incorporates cutting-edge AI technology, including machine
learning, machine-assisted discovery, and a high-performance database
system to automatically measure and classify the billions of objects in
the sky survey images, and to assist astronomers in performing scientific
analyses of the resulting catalogs.
The Caltech group used SKICAT to select quasar candidates from
catalogs of objects detected in the sky survey, sorting through roughly
one million other objects to find each quasar. On photographs, quasars
are indistinguishable from ordinary stars in our galaxy.
'This is far more difficult than finding needles in a haystack,' said
Kennefick. 'SKICAT allows us to automatically sort through and pinpoint
interesting quasar candidates based on their color, so that we can make
the best possible use of the valuable telescope time in checking them
out.' A previous survey for quasars at comparable distances done at
Palomar used about 20 times more nights, with the 200-inch Hale Telescope,
and found only nine quasars.
'This great increase in the observing efficiency is due to a
combination of the huge amount of data in the sky survey, and the modern
software techniques that allow us to explore it,' Djorgovski said. 'And
the more quasars we find, the better we will be able to map these early
epochs of the universe.'
'Data mining and automated analysis of large databases offer the
promise of giving us a handle on the data avalanche generated by NASA
instruments on missions to planet earth and elsewhere in the solar
system,' said Mel Montemerlo, the manager of the Autonomy and Operations
Program at NASA headquarters in Washington, DC.
This work was supported by the National Aeronautics and Space
Administration, with additional funding from the National Science
Foundation.
# # #
Technical contacts:
at JPL: Dr. Usama Fayyad fayyad@aig.jpl.nasa.gov
Machine Learning Systems Group
Jet Propulsion Lab 525-3660
California Institute of Technology
Pasadena, CA 91109
U.S.A.
at Caltech: Prof. George Djorgovski george@deimos.caltech.edu
Astronomy/Palomar Observatory
California Institute of Technology
Pasadena, CA 91125
U.S.A.
# # # Previous2NextTop
>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Return-Path: (simoudis@almaden.ibm.com)
Date: Sat, 30 Dec 1995 17:07:56 -0800
From: (simoudis@almaden.ibm.com)
(Evangelos Simoudis)
Subject: for the nuggets
On 12/30 IBM premiered one TV commercial on the topic of data mining.
This commercial was first aired during the NFL wildcard game and is
under IBM's successful ad campaign entitled 'Solutions for a Small
Planet.' People who have seen other ads of this campaign, e.g, the
nuns, the greek sponge divers, etc, will recognize the whimsical
nature of it.
Anyway, we would be very interested on the feedback of the people who
have seen the ad since more will follow. Please send your comments to
me (simoudis@almaden.ibm.com),
or send mail via our home page http://www.almaden.ibm.com/stss/.
Regards
Evangelos
Previous3NextTop
>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Date: Sun, 17 Dec 1995 20:03:44 +2000
Sender: Inductive Learning Group (INDUCTIVE@hermes.csd.unb.ca)
From: Automatic digest processor (LISTSERV@hermes.csd.unb.ca)
Date: Sat, 16 Dec 1995 16:29:31 -0400
From: Robert Andrews (robert@fit.qut.edu.au)
Subject: Rule Extraction Mailing List
=-=-=-=-= RULE EXTRACTION FROM ARTIFICIAL NEURAL NETWORKS =-=-=-=-=-=-=-=-
ANNOUNCEMENT OF MAILING LIST
Rule Extraction from Artificial Neural Networks and the related field of
Rule Refinement are topics of increasing interest and importance. This is to
announce the formation of a moderated mailing list for researchers and
students interested in these areas.
If you are interested in becoming a subscriber to this list please send the
following information by return mail:
Mr Robert Andrews
School of Information Systems robert@fit.qut.edu.au
Faculty of Information Technology R.Andrews@qut.edu.au
Queensland University of Technology +61 7 864 1656 (voice)
GPO Box 2434 _--_| +61 7 864 1969 (fax)
Brisbane Q 4001 / QUT
Australia _.--._/ http://www.fit.qut.edu.au/staff/~robert
v Previous4NextTop
>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
(via NN-digest)
Subject: NN Benchmarking WWW homepage
From: Lutz Prechelt (prechelt@ira.uka.de)
Date: Mon, 11 Dec 1995 13:11:32 +0100
The homepage of the very successful NIPS*95 workshop on benchmarking
has now been converted into a repository for information about
benchmarking issues: Status quo, methodology, facilities, and
related info.
I kindly ask everybody who has additional information that should
be on the page (in particular sources or potential sources of
learning data of all kinds) to submit that information to me.
Other comments are also welcome.
The page is also still reachable over the benchmarking workshop
link on the NIPS*95 homepage.
Below is a textual version of the page.
Lutz
Lutz Prechelt http://wwwipd.ira.uka.de/~prechelt/
| Whenever you
Institut f. Programmstrukturen und Datenorganisation | complicate things,
Universitaet Karlsruhe; D-76128 Karlsruhe; Germany | they get
(Phone: +49/721/608-4068, FAX: +49/721/694092) | less simple.
Previous5NextTop
>~~~Publications:~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
From: JAMAJOR@delphi.com
Date: Tue, 02 Jan 1996 12:53:20 -0500 (EST)
Subject: New Wiley book on intelligent systems
Content-Length: 565
_Intelligent Systems for Finance and Business_ edited by Suran Goonatilake
and Philip Treleaven has just been published by John Wiley and Sons.
Its theme is 'a category of computing devices that can find patterns and
discover relationships in large amounts of data.' Each chapter is a self-
contained paper describing an application. Techniques include neural nets,
fuzzy logic, genetic algorithms, inductive learning, statistics, etc.
Application domains include credit evaluation, direct marketing, insurance
fraud detection, securities trading, and economics.
Date: Tue, 19 Dec 1995 18:36:56 -0800 (PST)
From: 'Padhraic J. Smyth' (pjs@aig.jpl.nasa.gov)
To: kdd@gte.com
Subject: Preliminary CFP for 1996 CSNA/NT Meeting
Content-Type: text
Content-Length: 3110
CALL FOR PAPERS: JOINT 1996 ANNUAL MEETING OF THE
CLASSIFICATION SOCIETY OF NORTH AMERICA AND THE NUMERICAL
TAXONOMY GROUP, June 13-16,1996, to be held at the
University of Massachusetts, Amherst, MA 01003, USA
The 1996 annual meeting of the Classification Society of
North America will be held jointly with the Numerical
Taxonomy Group at the Campus Center Hotel which is located
in the center of the University of Massachusetts Campus.
Both hotel and dormitory facilities will be available.
Several restaurants are located in the hotel complex.
A more detailed announcement will be available in
December, 1995. A short course will be held on Thursday,
June 13, and there will be a welcoming reception that
evening. Friday will consist of CSNA sessions, followed
by the CSNA business meeting and a banquet. On Saturday,
June 15, the morning will be devoted to CSNA sessions,
while the afternoon will have joint sessions with the NT
group, followed by an NT reception. The NT sessions will
continue with a session on Sunday, and end early Sunday
afternoon with the NT business meeting.
These meetings are traditionally both informal and
interdisciplinary, with few (if any) parallel sessions.
Abstracts of papers will be distributed, but there will be
no formal proceedings of the conference. Speakers often
discuss work in progress, as well as ideas for future
research. A mix of applications, methodology and
theoretical results are usually represented.
Sessions tentatively planned include:
General consensus theory.
Pathfinder networks and proximity graphs
Classification in Social Network Analysis
Graduate student session.
Information retrieval.
Image analysis and estimation
Biological applications of consensus theory.
Reticulate evolution.
Keynote speakers will include Herman Friedman of Fordham University,
Donald Geman of the University of Massachusetts, Bruno Leclerc of
C.A.M.S., Paris, Philippa Pattison of the Univerity of Melbourne, and
D. L. Swofford of the Smithsonian Institution.
The organizers of the meeting encourage the presentation of
contributed papers that cover a wide range of applications
and methodology that involve exploratory data analysis
viewed in its broadest sense. Papers related to evolution
and molecular biology are of particular interest to the
numerical taxonomy group. Short abstracts of papers should
be sent to the appropriate program chair, as well as any
suggestions for symposia, special sessions, topics, panel
discussions, requests for further information, or other
contributions. The deadline for submission of abstracts is
March 15, 1996. The program chair for the CSNA program is
Melvin F. Janowitz, Department of Mathematics and
Statistics, University of Massachusetts, Amherst, MA 01003
USA, telephone (413)-545-2871, Fax (413)-545-1801, e-mail
csna96@math.umass.edu.
The program director for the NT
meeting is Pierre Legendre, Department de sciences
biologiques, Universite de Montreal, C.P. 6128, succursale
Centre-ville, Montreal, Quebec, Canada H3C 3J7, telephone
(514)-343-7591, fax (514)-343-2293, e-mail
legendre@ere.umontreal.ca.
Previous7NextTop
>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Date: Fri, 22 Dec 1995 13:55:48 +0900
From: tsumoto@tmd.ac.jp
(Shusaku Tsumoto)
Subject: Re: CFP for Workshop on Rough Sets
**** C A L L F O R P A P E R S ****
THE FOURTH INTERNATIONAL WORKSHOP ON
ROUGH SETS, FUZZY SETS AND MACHINE DISCOVERY (RSFD'96)
The University of Tokyo
Hongo,
Tokyo, JAPAN
November 6-8, 1996
---------------------------------------------------------------------------
Sponsored by: Information Processing Society of Japan
In Cooperation with
* International Rough Set Society(IRSS)
* Institute of Electronics, Information and Communication
Engineers of Japan (IEICE)
* Japanese Society for Artificial Intelligence (JSAI)
* Society of Instrument and Control Engineers of Japan (SICE)
* Japan Society for Fuzzy Theory and Systems
* Japan Research Group on Multiple-Valued Logic
Supported by: Inoue Foundation for Science
Rough sets and fuzzy sets are complementary generalizations of classical
sets. The rapid developments of these two approaches form a beginning of
a 'soft mathematics' and provide a basis for 'soft computing', which
includes, along with rough sets, fuzzy logic, neural networks,
probabilistic reasoning, belief networks, learning,
connectionist computing, genetic algorithms.
Machine Discovery is also a growing area, encompassing knowledge
discovery in databases, discovery of regularities (such as
rules, dependencies, empirical equations),
causal structures by using methods of database theory,
artificial intelligence (including machine learning),
rough sets and statistics.
This workshop will allow researchers to present their recent research
results and to exchange their views of
rough sets, fuzzy sets, and machine discovery.
The exchange should lead to mutually beneficial co-operation.
PAPER SUBMISSION
Electronic submissions are strongly encouraged.
Authors are invited to submit four copies of their
manuscript (maximum 10 pages) to:
Address: Akira Nakamura
Department of Computer Science,
Meiji University
1-1-1, Higashi-mita, Tama-ku
Kawasaki 214
Japan
May 31: Submission Deadline
July 15: Acceptance Letters (e-)mailed
September 15: Deadline for the Final Manuscript
October 10: Advance registration
November 6-8, Workshop Technical Sessions held
WORKSHOP HISTORY
The First International Workshop on 'Rough Sets: State of the Art
and Perspectives' took place in Kiekrz, Poland on September 2-4,
1992. The 'Second International Workshop on Rough Sets and Knowledge
Discovery' (RSKD'93) was held in Banff, Canada in October 12-15, 1993.
The 'Third International Workshop on Rough Sets and Soft Computing'
(RSSC'94) was held in San Jose, California, USA in November 10-12, 1994.
The workshops demonstrated the far reaching consequences of rough
set theory both in theoretical and empirical sciences.
The participants of the workshops were
a true mixture of pure theorists and down-to-
earth practitioners, reflecting the interdisciplinary character
of the theory of rough sets .
WORKSHOP FORMAT
The workshop is planned as a three-day interdisciplinary conference
focused on various theoretical, methodological, and practical aspects
of rough sets, fuzzy sets and machine discovery. It will be a
combination of invited talks, oral and poster presentations,
and a series of 'round-table' discussions intended to stimulate
the development of interdisciplinary understanding. The format will
include the presentation of the fundamentals of rough sets, fuzzy sets
and machine discovery as well as will provide ample time
for discussion and the exchange of ideas.
The following themes are planned for workshop sessions:
1. Fundamentals of Rough Sets, Fuzzy Sets, and Machine Discovery
2. Logic Systems for Reasoning under Uncertainty
3. Probabilistic and Statistical Reasoning.
4. Knowledge Discovery and Data Mining
5. Machine Learning
6. Fuzzy and Rough Control Theory
7. Discovery of Regularities, Concepts and Taxonomies in Databases
8. Integrated treatment of Uncertain, Fuzzy, and Indiscernible
Data and Knowledge
9. Automated Data Analysis: Combining Search with Statistics,
Search for empirical equations and other patterns in Data
10. Successful usage of Machine Discovery in Medicine, Biochemistry,
Business and Industry
11. Other Applications of Rough Sets, Fuzzy Sets and Machine Discovery
TUTORIALS AND SYSTEM DEMONSTRATIONS
Tutorial and system demonstrations are also planned. Participants
willing to demonstrate software should contact Akira Nakamura at
nakamura@cs.meiji.ac.jp
by September 1, 1996.
Publicity: Y.Y. Yao , North America, yyao@thunder.lakeheadu.ca
J. Stefanowski, Europe, stefanj@pozn1v.tup.edu.pl
T. Yokomori, Asia, yokomori@base.cs.uec.ac.jp
STEERING COMMITTEE
Z. Pawlak
R. Slowinski
W. Ziarko
T.Y. Lin
J. Grzymala-Busse
A. Nakamura
S. Tsumoto
J. Zytkow
PROGRAM COMMITTEE
James Bezdek, University of West Florida, U.S.A.
Nick Cercone, University of Regina, Canada
Didier Dubois, Universite Paul-Sabatier CNRS, France
Jerzy Grzymala-Busse, University of Kansas, U.S.A.
Mitsuru Ishizuka, The University of Tokyo, Japan
Willi Kloesgen, GMD, Germany
Satoshi Kobayashi, The University of Electrocommunication, Japan
Shigenobu Kobayashi, Tokyo Institute of Technology, Japan
T.Y. Lin, San Jose State University, U.S.A.
Ryszard Michalski, George Mason University, U.S.A.
Masao Mukaidono, Meiji University, Japan
Toshinori Munakata, Cleveland State University, U.S.A.
Hiroshi Motoda, Hitachi Research Laboratory, Japan
Kaoru Hirota, Tokyo Institute of Technology, Japan
Masahiro Inuiguchi, Hiroshima University, Japan
Kazuo Nakamura, Nagaoka University of Technology, Japan
Charles Nguyen, Catholic University of America, U.S.A.
Masayuki Numao, Tokyo Institute of Technology, Japan
Zdzislaw Pawlak, Warsaw University of Technology, Poland
Zbigniew Ras, University of North Carolina, U.S.A.
Andrzej Skowron, Warsaw University, Poland
Gregory Piatetsky-Shapiro, GTE Laboratories, U.S.A.
Krzysztof Slowinski, K.Marcinkowski University of Medical Sciences, Poland
Roman Slowinski, Technical University of Poznan, Poland
Jerzy Stefanowski, Technical University of Poznan, Poland
Roman Swiniarski, San Diego State University, U.S.A.
Hideo Tanaka, Universiy of Osaka Prefecture, Japan
Raul Valdes-Perez, Carnegie Mellon University, U.S.A.
Anita Wasilewska, State University of New York, U.S.A.
Michael Wong, University of Regina, Canada
Yiyu Yao, Lakehead University, Canada
Takahira Yamaguchi, Shizuoka University, Japan
Wojciech Ziarko, University of Regina, Canada
Jan Zytkow, Wichita State University, U.S.A.
PUBLICATION
The proceedings will be distributed to all registered participants
at the workshop.
Moreover, the best selected papers are considered to
include in the special volume of academic journals.
+----------------------------------------------------------------------+
| |& %| | Shusaku Tsumoto |
| | & % | |~~| | Assistant Professor |
| | V | |~~|& | Department of Information Medicine |
| Medical Research Institute |
| TEL: +81-3-5803-5840 Tokyo Medical and Dental Unversity |
| FAX: +81-3-5803-0247 1-5-45 Yushima, Bunkyo-city, |
| E-mail: tsumoto@cmn.tmd.ac.jp
Tokyo 113 Japan |
| << Forever Voyaging ....>> |
+----------------------------------------------------------------------+
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