--
Discovery in Databases (KDD) community, focusing on the latest research and
applications.
Submissions are most welcome and should be emailed,
with a DESCRIPTIVE subject line (and a URL, when available) to kdd@gte.com
To subscribe, email to kdd-request@gte.com
message with
subscribe kdd-nuggets
in the first line (the rest of the message and subject are ignored).
See
Nuggets frequency is approximately 3 times a month.
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
********************* 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 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
'If at first you don't succeed, try again.
Then quit. No use being a fool about it.' --dilbert's laws of work
Previous1NextTop
From: Rob Gerritsen (rob@twocrows.com)
Subject: Two Crows data mining site now open on the Web
Date: Thu, 2 Jan 1997 21:30:46 -0500
Encoding: 15 TEXT
Content-Length: 703
Two Crows Corporation has opened a web site dedicated to data mining at
Two Crows Corporation is currently completing a multi-client study entitled
Knowledge Discovery and Data Mining: Products and Markets. The study
includes hands-on evaluations of more than a dozen data mining products and
the results of a wide-ranging survey of trends in data mining. Two Crows
plans to publish the results of the study before the end of the 1st
quarter.
To get more information about this study, to review a recent white paper on
Scalable Strength Data Mining, or for a useful links page to commercial
data mining sites on the web, please visit us at
High quality, original papers that deal with real-world problems
are solicitated. All the submitted manuscripts will be subject
to a rigorous review process. Manuscripts should be prepared in
accordance with the IEEE Expert 'submission guidelines'.
Manuscripts should be approximately 5,000 words long, preferably
not exceeding 10 references. This special issue is scheduled to
appear in late 1997.
Important Dates:
Submission April 30 (FIRM DEADLINE)
Notification June 30
Prospective authors should submit six copies of the completed
manuscript to one of the guest editors:
Huan Liu Hiroshi Motoda
S16 #4-17 Institute of Scientific & Industrial
Dept of Info Sys & Comp Sci Research
National University of Singapore Osaka University
Kent Ridge, Singapore, 119260 Ibaraki, Osaka 567, Japan
liuh@iscs.nus.sg
motoda@sanken.osaka-u.ac.jp
Previous3NextTop
From: Ivan Pulleyn (ivan@magnify.com)
Subject: KDD positions at Magnify, Incorporated
Date: Thu, 2 Jan 1997 19:28:54 -0600 (CST)
------------------------------------------------------------------------------
The following KDD related positions are available at Magnify, Incorporated.
------------------------------------------------------------------------------
Position: Project Leader/Sr. Developer
Magnify, Inc. is a rapidly growing Chicago based company which is a
leader in the development of scalable and high performance data mining
systems and software. Magnify develops data mining software for
financial services, defense systems, and related sectors.
Description: Provide rapid development leadership for PATTERN data
mining system. Oversee and participate in our development effort, with
the goal of expanding the scalability, extensibility, and capabilities
of our software. Lead a dedicated enthusiastic team, while setting the
pace by directly participating in the software development process.
Deliver highly competitive real-world vertical market solutions.
Required Skills:
* 4-5 years experience in data mining, high performance computing,
object oriented databases, or related areas
* Experience delivering robust commercial software to market on time
and within budget
The work is challenging, with opportunities to be creative. Good
working conditions and benefits. Please email resumes to
jobs@magnify.com
or fax to 708 383 7084.
Magnify is an affirmative action/equal opportunity employer and strives
for diversity in its work force.
Magnify, Inc. is a rapidly growing Chicago based company which is a
leader in the development of scalable and high performance data mining
systems and software. Magnify develops data mining software for
financial services, defense systems, and related sectors.
Description: Design and develop next generation data mining system.
Develop data cleaning and data transformation tools. Implement and
evaluate the performance of parallel data mining algorithms. Develop and
implement new data mining algorithms.
Required Skills:
* Strong C++/UNIX
* Strong applied mathematics/statistics background. M.S. or
Ph.D preferred.
* Parallel and distributed algorithm design
* Expertise in at least two standard data mining methods (i.e.
tree-based, neural networks, Bayesian methods, clustering, etc.)
The work is challenging, with opportunities to be creative. Good
working conditions and benefits. Please email resumes to
jobs@magnify.com
or fax to 708 383 7084.
Magnify is an affirmative action/equal opportunity employer and strives
for diversity in its work force.
Magnify, Inc. is a rapidly growing Chicago based company which is a
leader in the development of scalable and high performance data mining
systems and software. Magnify develops data mining software for
financial services, defense systems, and related sectors.
Description: Develop next generation data mining system. Enhance persistent
object layer of client/server architecture. Build transparent interface to
relational databases and data warehouses. Implement scalable data management
methods that fulfill data mining requirements.
Required skills:
* 2-3 years experience with data warehouses, object-relational
databases, object oriented databases, or related areas.
* experience with mainframe databases and mainframe/unix system integration
desired
The work is challenging, with opportunities to be creative. Good
working conditions and benefits. Please email resumes to
jobs@magnify.com
or fax to 708 383 7084.
Magnify is an affirmative action/equal opportunity employer and strives
for diversity in its work force.
Magnify, Inc. is a rapidly growing Chicago based company which is a
leader in the development of scalable and high performance data mining
systems and software. Magnify develops data mining software for
financial services, defense systems, and related sectors.
Description: Provide on-site consulting and training for data mining
application solutions. Monitor on-site data mining process to ensure data
mining requirements are met.
Required skills:
* strong communication skills required
* applied mathematics/statistics experience
* comfortable in UNIX environment. Perl/shell scripting skills a plus.
* experience consulting for decision support software
The work is challenging, with opportunities to be creative. Good
working conditions and benefits. Please email resumes to
jobs@magnify.com
or fax to 708 383 7084.
Magnify is an affirmative action/equal opportunity employer and strives
for diversity in its work force.
--
Ivan Pulleyn Magnify, Inc. home:
ivan@magnify.com
815 Garfield Street 1401 North Bosworth Avenue
Oak Park, IL 60304 Chicago, IL 60622
708 383-7002 773-278-5902 Previous4NextTop
Date: Wed, 8 Jan 1997 11:00:10 -0500
From: gps@gte.com
(Gregory Piatetsky-Shapiro)
Subject: Data Mining Summit, San Francisco, Feb 18-21, 1997
Data Mining Summit, San Francisco, Feb 18-21, 1997
will present a number of invited talks and presentations
by leaders of the field. Full information at
Previous5NextTop
Date: Wed, 11 Dec 1996 10:59:32 -0500
From: ras@uncc.edu
(Zbigniew W Ras)
Subject: ISMIS'97 Call for Papers
**** C A L L F O R P A P E R S ****
TENTH INTERNATIONAL SYMPOSIUM ON
METHODOLOGIES FOR INTELLIGENT SYSTEMS (ISMIS'97)
Hilton Hotel, Charlotte, North Carolina
October 15-18, 1997
SPONSORS
UNC-Charlotte, Oak Ridge National Laboratory, Univ. of Warsaw, and others.
PURPOSE OF THE SYMPOSIUM
This Symposium is intended to attract individuals who are actively
engaged both in theoretical and practical aspects of intelligent systems.
The goal is to provide a platform for a useful exchange between
theoreticians and practitioners, and to foster the cross-fertilization
of ideas in the following areas:
* Evolutionary Computation
* Intelligent Information Systems
* Learning and Knowledge Discovery
* Knowledge Representation and Integration
* Logic for Artificial Intelligence
* Robotics, Motion and Machine Vision
* Soft Computing
* Methodologies (modeling, design, validation, performance evaluation).
In addition, we solicit papers dealing with Applications of Intelligent
Systems in complex/novel domains, e.g. human genome, global change,
manufacturing, health care, etc.
SYMPOSIUM CHAIRS
Francois G. Pin (Oak Ridge National Lab.)
Zbigniew W. Ras (UNC-Charlotte & Polish Acad. Sci.)
Andrzej Skowron (U. Warsaw, Poland)
PROGRAM COMMITTEE
Luigia Carlucci Aiello (U. Roma, Italy)
Thomas Baeck (Inf. Centrum Dortmund & U. Leiden, The Netherlands)
Alan Biermann (Duke Univ.)
Jacques Calmet (U. Karlsruhe, Germany)
Jaime Carbonell (CMU)
Wesley Chu (UCLA)
Kenneth DeJong (GMU)
Robert Demolombe (CERT/ONERA, France)
Jon Doyle (MIT)
Toshio Fukuda (Nagoya U., Japan)
Attilio Giordana (U. Torino, Italy)
Diana Gordon (Naval Research Lab.)
Mirsad Hadzikadic (Carolinas HealthCare System)
Jiawei Han (Simon Fraser U., Canada)
David Hislop (Army Research Office)
Matthias Jarke (RWTH Aachen, Germany)
John Y. Jiang (Pacific Bell Lab.)
Willi Kloesgen (GMD, Germany)
Yves Kodratoff (U. Paris VI, France)
Jan Komorowski (U. Trondheim, Norway)
Alberto Martelli (U. Torino, Italy)
Robert Meersman (U. Brussels, Belgium)
Zbigniew Michalewicz (UNC-Charlotte & Polish Acad. Sci.)
Ryszard Michalski (GMU & Polish Acad. Sci.)
Jack Minker (U. Maryland)
Ephraim Nissan (U. Greenwich, UK)
Lin Padgham (RMIT U., Australia)
Rohit Parikh (CUNY)
Lynne Parker (ORNL)
Gregory Piatetsky-Shapiro (GTE Lab.)
Henri Prade (U. Paul Sabatier, France)
Luc De Raedt (U. Leuven, Belgium)
Marek Rusinkiewicz (MCC)
Lorenza Saitta (U. Torino, Italy)
Erik Sandewall (Linkoping U., Sweden)
Yoav Shoham (Stanford U.)
Richmond Thomason (U. Pittsburgh)
Jing Xiao (UNCC)
Carlo Zaniolo (UCLA)
Gian Piero Zarri (CNRS, France)
Maria Zemankova (NSF)
Jan M. Zytkow (Wichita State U. & Polish Acad. Sci.)
ORGANIZING COMMITTEE
Brian Bachman (First Union)
Mirsad Hadzikadic (Carolinas HealthCare System)
Karen Harber (ORNL)
Mieczyslaw Klopotek (Polish Acad. Sci.)
M.S. Narasimha (IBM-Charlotte)
Zbigniew W. Ras (UNC-Charlotte)
PAPER SUBMISSION
Authors are invited to submit four copies of their manuscript
(maximum 12 pages) to one of the addresses below:
Papers from US and Canada: Papers from Europe:
Francois G. Pin, ISMIS'97 Andrzej Skowron, ISMIS'97
ORNL, Bldg. 7601, M.S. 6305 Univ. of Warsaw
P.O. Box 2008 Dept. of Mathematics
Oak Ridge, TN 37831-6305 Banacha 2
e-mail: pin@ORNL.GOV
PL-02-097 Warsaw, POLAND
fax: 423-574-4624 e-mail: skowron@mimuw.edu.pl
tel: 423-574-6130 tel: 48-(22)-658-3449
All other papers:
Zbigniew W. Ras, ISMIS'97
Univ. of North Carolina
Dept. of Comp. Science
Charlotte, N.C. 28223
e-mail: ras@uncc.edu
fax: 704-547-3516
tel: 704-547-4567
Submissions should include a title page (1 copy) specifying the
title, all authors with their affiliations, abstract (100-200 words),
up to 10 keywords (begin the keyword list with at least one of the
ISMIS areas listed above); and the preferred address of the contact
author, including a telephone number, fax number, and e-mail address
(if available). The remainder of the paper can include up to 11 pages,
attached to the title page.
If possible, the title page should be ADDITIONALLY submitted via email
(in plain text) to (ras@uncc.edu)
to facilitate submissions processing.
IMPORTANT DATES
Submission of Papers: March 1, 1997
Acceptance Notification: May 25, 1997
Final Paper: July 1, 1997
PUBLICATION
Papers accepted for Regular Sessions will be published by
Springer-Verlag in LNCS/LNAI.
Poster Session proceedings will be published by Oak Ridge
National Laboratory.
Both proceedings will be available at the symposium.
Previous6NextTop
Date: Fri, 3 Jan 97 21:23:46 CST
From: jan zytkow (zytkow@deanna.cs.twsu.edu)
Subject: PKDD-97 CFP: please distribute
Content-Length: 7494
PKDD'97 -- 1st European Symposium on Principles of
Data Mining and Knowledge Discovery
Trondheim, Norway
June 25-27, 1997
Data Mining and Knowledge Discovery (KDD) have recently emerged from a
combination of many research areas: databases, statistics, machine
learning, automated scientific discovery, inductive 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'97 is to provide a European-based forum for
interaction among all theoreticians and practitioners interested in
data mining. Fostering an interdisciplinary collaboration is one
desired outcome, but the main long-term focus is on theoretical
principles for the emerging discipline of KDD, especially those new
principles that go beyond each of the contributing areas.
To promote these goals, PKDD'97 will be organized into tracks around
the key areas contributing to KDD. For each area an ideal paper
should focus on how its methods advance KDD's goals and principles.
Both theoretical and applied submissions are sought. Reviewers will
assess the contribution towards the main goals of PKDD'97, in addition
to the usual requirements of novelty, clarity and significance.
Applied papers should go beyond an individual application, presenting
an explicit method that promises a degree of generality within some
stage of the discovery process, such as preprocessing, mining,
visualization, use of prior knowledge, knowledge refinement, and
evaluation. Theoretical papers should demonstrate how they advance
the process of data mining and knowledge discovery.
The following non-exclusive list exemplifies topics of interest:
Data and knowledge representation for data mining
* Beyond relational databases: new forms of data organization
* Data reduction
* Prior domain knowledge and use of discovered knowledge
* Combining query systems with discovery capabilities
Statistics and probability in data mining
* Discovery of probabilistic networks
* Modeling data and knowledge uncertainty
* Discovery of exceptions and deviations
* Statistical significance in large-scale search
* The problems of over-fit
Logic-based perspective on data mining
* Inferring knowledge from data
* Exploring different subspaces of first order logic
* Rough sets in data mining
* Fuzzy sets in data mining
* Boolean approaches to data mining
* Inductive Logic Programming for mining real databases
* Pattern-recognition for data mining
* Clustering analysis
* Tolerance (similarity) relations
* KDD-motivated discretization of data
Man-Machine interaction in data mining
* Visualization of data
* Visualization of results
* Interface design
* Interactive data mining: human and computer contributions
Artificial Intelligence contributions to KDD
* Representing knowledge and hypotheses spaces
* Search for knowledge and its complexities
* Combining many methods in one system
High performance computing for data mining
* Hardware dedicated to discovery applications
* Parallel discovery algorithms and complexity
* Distributed data mining
* Scalability in high dimensional datasets
From machine learning to KDD
* From concept learning to concept discovery
* Expanding the autonomy of machine learners
* Embedding learning methods in KDD systems
* Conceptual clustering in knowledge discovery
From automated scientific discovery to KDD
* Applications of scientific discovery systems to databases
* Experience with hypothesis evaluation that transfers to KDD
* Hypothesis spaces of scientific discovery applied in KDD
* Differences between the data handled in both fields
* Scientific discovery techniques relevant in KDD
Quality assessment of data mining results
* Multi-criteria knowledge evaluation
* Benchmarks and metrics for system evaluation
* Statistical tests in KDD applications
* Usefulness and risk assessment in decision-making
Applications of data mining and knowledge discovery
* Medicine: diagnosis and prognosis
* Control theory: predictive and adaptive control, model identification
* Engineering: diagnosis of mechanisms and processes
* Public administration
* Marketing and finance
* Data mining on the web in text and heterogeneous data
* Natural and social science
Submissions are by email (preferred) to pkdd97@idt.ntnu.no
or by
airmail to Jan Komorowski (see address below). Papers should be in
English and not exceed ten single-spaced pages of 12pt font. The
first page should begin with title, authors, affiliations, surface and
e-mail addresses, and an abstract of about 200 words.
Important dates -
Submission deadline: February 5th, 1997
Notice of acceptance: March 3rd
Camera ready papers: March 23rd
PANEL DISCUSSIONS: proposals are sought for panels that stimulate
interaction between the communities contributing to KDD. Include
title prospective participants and a summary of the topics to be
discussed. Submission to zytkow@cs.twsu.edu
by March 14th. Notice of
acceptance by March 21th.
POSTER SESSION: informative descriptions of successful applications of
data mining and knowledge discovery techniques in processing new data
sets may be submitted for presentation at the poster session. Send an
extended abstract, not exceeding two pages of 12pt, single spaced text
to pkdd97@idt.ntnu.no
by March 14th. Notice of acceptance by March
21st.
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 pkdd97@idt.ntnu.no
by February 19th.
Notice of acceptance by March 10th.
DEMONSTRATIONS OF SOFTWARE for data mining and knowledge discovery are
invited, including both professional and experimental systems. Send
descriptions to pkdd97@idt.ntnu.no
by June 2nd.
Program co-chairs:
Jan Komorowski, Trondheim, Norway Jan Zytkow, Wichita, USA
Jan.Komorowski@idt.ntnu.no
zytkow@cs.twsu.edu
Department of Computer Systems
Norwegian University of Science and Technology
7034 Trondheim, Norway
Program Committee:
Pieter Adriaans (Syllogic, Netherlands)
Attilio Giordana (U. Torino, Italy)
David Hand (Open U. UK)
Bob Henery (U. Strathclyde, UK)
Mikhail Kiselev (Nat.Research Center of Surgery, Russia)
Willi Kloesgen (GMD, Germany)
Yves Kodratoff (U. Paris VI, France)
Heikki Mannila (U. Helsinki, Finland)
Marjorie Moulet (LRI, U. Paris XI, France)
Steve Muggleton (Oxford U. UK)
Zdzislaw Pawlak (Warsaw Technical U. Poland)
Gregory Piatetsky-Shapiro (GTE Lab. USA)
Zbigniew Ras (UNC Charlotte, USA)
Erik Sandewall (Linkoping U., Sweden)
Lorenza Saitta (U. Torino, Italy)
Wei-Min Shen (U. So. California, USA)
Arno Siebes (CWI, Netherlands)
Andrzej Skowron (U. Warsaw, Poland)
Derek Sleeman (U. Aberdeen, UK)
Shusaku Tsumoto (Tokyo Medical & Dental U. Japan)
Raul Valdes-Perez (CMU, USA)
Rudiger Wirth (Daimler-Benz, Germany)
Stefan Wrobel (GMD, Germany)
Wojtek Ziarko (U. Regina, Canada)
Details regarding the conference will be forthcoming. Watch the
PKDD'97 WWW page for details
Previous7NextTop
Date: Mon, 6 Jan 97 11:19:19 EST
From: Sal Stolfo (sal@cs.columbia.edu)
Subject: Workshop on R&D Opportunities in Federal Information Services
technologies and Data Mining and hence this anouncement is likely of
interest to this community.>
A workshop on R&D Opportunities in Federal Information Services is
being sponsored by the Applications Council of the National Science and
Technology Council's Committee on Computing, Information, and
Communications and is being coordinated by the Information Sciences
Institute of the University of Southern California. Funding for
conducting the workshop has been provided by the National Science
Foundation's Directorate for Computer and Information Science and
Engineering, the President's Government Information Technology Services
Board, and National Institutes of Health's National Center for Research
Resources. The workshop is scheduled for May 13-15, 1997 to be held at
a location to be determined in or near Washington, D.C.
As a result of the first meeting (December 3-4) of the organizing
committee for the workshop, a Call for White Papers has been developed.
The Call and additional information on the workshop process can be
found at URL
. This URL will be kept live and
dynamic as more information is available, and will serve as the entry
point for on line submission of White Papers beginning in mid-January
1997. Papers are due no later than March 3, 1997.
All sectors and interested parties are encouraged to submit Papers for
review. Please forward this message to any interested individuals or
organizations.
Thank you.
Lawrence E. Brandt
Program Manager for Advanced Information Systems
Division of Advanced Scientific Computing, Room 1122
Knowledge Discovery Nuggets Index