--
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 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Lo! Men have become the tools of their tools.
- Henry David Thoreau Previous1NextTop
>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Return-Path: (datamine@aig.jpl.nasa.gov)
Date: Mon, 15 Jan 96 13:44:31 PST
From: datamine@aig.jpl.nasa.gov
(Data Mining Journal)
Subject: New Journal -- Data Mining and Knowledge Discovery
New Journal Announcement:
Data Mining and Knowledge Discovery
an international journal
C a l l f o r P a p e r s
****************************************************************
Advances in data gathering, storage, and distribution technologies have far
outpaced computational advances in techniques for analyzing and understanding
data. This created an urgent need for a new generation of tools and
techniques for automated Data Mining and Knowledge Discovery in Databases
(KDD). KDD is a broad area that integrates methods from several fields
including statistics, databases, AI, machine learning, pattern recognition,
machine discovery, uncertainty modeling, data visualization, high performance
computing, management information systems (MIS), and knowledge-based systems.
KDD refers to a multi-step process that can be highly interactive and
iterative. It includes data selection/sampling, preprocessing and
transformation for subsequent steps. Data mining algorithms are then used
to discover patterns, clusters and models from data. These patterns and
hypotheses are then rendered in operational forms that are easy for people
to visualize and understand. Data mining is a step in the overall KDD
process. However, most published work has focused solely on
(semi-)automated data mining methods. By including data mining explicitly
in the name of the journal, we hope to emphasize its role, and build bridges
to communities working solely on data mining.
Our goal is to make Data Mining and Knowledge Discovery a flagship journal
publication in the KDD area, providing a unified forum for the KDD research
community, whose publications are currently scattered among many different
journals. The journal will publish state-of-the-art papers in both the
research and practice of KDD, surveys of important techniques from related
fields, and application papers of general interest. In addition, there will
be a pragmatic section including short application reports (1-3 pages), book
and system reviews, and relevant product announcements.
Please visit the journal's WWW homepage at: http://www.research.microsoft.com/research/datamine/
to obtain further information, including:
- A list of topics of interest,
- full call for papers,
- instructions for submission,
- contact information, subscription information, and
- ordering a free sample issue.
Editors-in-Chief: Usama M. Fayyad
================ Jet Propulsion Laboratory,
California Institute of Technology, USA
Heikki Mannila
University of Helsinki, Finland
Gregory Piatetsky-Shapiro
GTE Laboratories, USA
Editorial Board:
===============
Rakesh Agrawal (IBM Almaden Research Center, USA)
Tej Anand (AT&T Global Information Solutions, USA)
Ron Brachman (AT&T Bell Laboratories, USA)
Wray Buntine (Thinkbank Inc, USA)
Peter Cheeseman (NASA AMES Research Center, USA)
Greg Cooper (University of Pittsburgh, USA)
Bruce Croft (University of Mass. Amherst, USA)
Dan Druker (Arbor Software, USA)
Saso Dzeroski (Jozef Stefan Institute, Slovenia)
Oren Etzioni (University of Washington, USA)
Jerome Friedman (Stanford University, USA)
Brian Gaines (University of Calgary, Canada)
Clark Glymour (Carnegie-Mellon University, USA)
Jim Gray (Microsoft Research, USA)
Georges Grinstein (University of Lowell, USA)
Jiawei Han (Simon Fraser University, Canada)
David Hand (Open University, UK)
Trevor Hastie (Stanford University, USA)
David Heckerman (Microsoft Research, USA)
Se June Hong (IBM T.J. Watson Research Center, USA)
Thomasz Imielinski (Rutgers University, USA)
Larry Jackel (AT&T Bell Labs, USA)
Larry Kerschberg (George Mason University, USA)
Willi Kloesgen (GMD, Germany)
Yves Kodratoff (Lab. de Recherche Informatique, France)
Pat Langley (ISLE/Stanford University, USA)
Tsau Lin (San Jose State University, USA)
David Madigan (University of Washington, USA)
Ami Motro (George Mason University, USA)
Shojiro Nishio (Osaka University, Japan)
Judea Pearl (University of California, Los Angeles, USA)
Ed Pednault (AT&T Bell Laboratories, USA)
Daryl Pregibon (AT&T Bell Laboratories, USA)
J. Ross Quinlan (University of Sydney, Australia)
Jude Shavlik (University of Wisconsin - Madison, USA)
Arno Siebes (CWI, Netherlands)
Evangelos Simoudis (IBM Almaden Research Center, USA)
Andrzej Skowron (University of Warsaw, Poland)
Padhraic Smyth (Jet Propulsion Laboratory, USA)
Salvatore Stolfo (Columbia University, USA)
Alex Tuzhilin (NYU Stern School, USA)
Ramasamy Uthurusamy (General Motors Research Laboratories, USA)
Vladimir Vapnik (AT&T Bell Labs, USA)
Ronald Yager (Iona College, USA)
Xindong Wu (Monash University, Australia)
Wojciech Ziarko (University of Regina, Canada)
Jan Zytkow (Wichita State University, USA)
======================================================================
If you would like to receive information from Kluwer on this journal,
and to receive a free sample issue by mail, please fill out the
form attached below, and e-mail it to datamine@aig.jpl.nasa.gov
Please use the following in SUBJECT field: REQUEST for SAMPLE J-DMKD
... Please do NOT remove keywords following '___', simply fill in provided
... fields and return as is. This form will be processed automatically.
... If you do not wish to complete a field, please LEAVE BLANK.
... Subject should be: REQUEST for SAMPLE J-DMK
... mail completed form, including keywords in CAPS to
... datamine@aig.jpl.nasa.gov
...
___ REQUEST FOR FREE SAMPLE ISSUE OF DATA MINING AND KNOWLEDGE DISCOVERY
___
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Previous2NextTop
>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Date: Mon, 15 Jan 1996 04:50:42 -0600
From: dfisher@vuse.vanderbilt.edu
(Douglas H. Fisher)
Subject: hard to find ML alg.
In research for an IEEE TSE article on estimating
software development effort, I came across an
article on the Optimized Set Reduction (OSR)
algorithm in IEEE TSE (Vol. 18, Nov. 1992).
The authors developed this system for
estimating software development effort from
a training set of completed software projects,
but the ideas are more general.
OSR retains a `training' set of observations,
each represented by attribute-value pairs.
When a test observation is presented, OSR
searches for conjunctive rules, supported
by the `training' data, that best match
the observation, and makes a prediction
by combining evidence from the various rules
that are discovered. It does not add discovered
rules to a `compiled' set of rules, but
conducts a new search for each test observation.
OSR's search might be viewed as a `beam' search
that is driven by an information measure.
There are some interesting relationships between
OSR and DL learners, particularly a system like
BruteDL. Looking at these systems together
seems to make two issues clear: (1) the
possibility of using evidence combination
in a DL system, rather than simply an
degenerate form of evidence combination
-- i.e., conflict resolution, and (2)
the relationship between macro learning
in problem solving contexts and conjunctive
rule learning in DL systems -- conjunctive
rules discovered during concept learning
are macro operators, though quite impoverished
given an attribute-value representation. A Masters
student recently completed a thesis in which OSR
was used as a default `strategy' (in place
of a default rule that is more standard in DLs)
in conjunction with BruteDL -- some interesting,
though modest results.
In any case, OSR is an interesting algorithm
that suggests some lines of work and that you might
not have otherwise come across. Id be interested
in refs. to any work along the `rules as macros'
theme.
Cheers, Doug Fisher Previous3NextTop
>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Date: Tue, 16 Jan 1996 08:31:27 -0800 (PST)
From: David Madigan (madigan@oscar.stat.washington.edu)
Subject: Bayesians Worldwide
I am assembling a list of Bayesian personal home pages. The nascent list
is at:
*Description: CrossGraphs combines cross-tabulation and
statistical graphics to produce graphical cross-tabulations
with many graphs per page, organized in rows and columns,
to help you discover relationships in higher-dimensional data and
compare patterns across many subsets of the data.
CrossGraphs supports over a dozen built-in graph
components, along with an ability to develop new kinds of custom graphs as
well. You can see graphical reports immediately on your computer screen or
produce presentation-quality printed reports for off-line review.
*Discovery methods: Visualization
*Comments:
*Platform(s): Windows 3.1, Windows95, Windows NT, SunOS, Solaris, HP-UX
*Contact: Jim Ong, Belmont Research, jong@belmont.com,
(617) 868-6878, fax: (617) 868-2654,
84 Sherman Street, Cambridge, MA 02140
*Status: in beta, production release scheduled for April 1996.
*Source of information: URL listed above, Belmont Research
Previous5NextTop
>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
From: cecil@pacific.net.sg
(Cecil Lee Gek Hian)
Date: Fri, 12 Jan 1996 18:08:04 +0800
Subject: Info on IDIS PC on the web
I've created a couple of web pages with info on IDIS PC.
The page contains some info on IDIS PC, a couple of screen captures,
a downloadable Lotus ScreenCam movie of IDIS PC running on a heart
disease database and an example of an automatically generated report
produced by IDIS PC summarising its findings after analysing the
discovered rules from analysing the heart disease database.
Comments on content, design, typos and any way the page can be
improved would be much appreciated.
Cheers,
Cecil
cecil@pacific.net.sg
Previous6NextTop
>~~~Positions:~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Newsgroups: comp.ai,comp.databases
From: tph@quasar.res.utc.com
(Tom Hamilton)
Subject: Job: Data Mining R&D at UTC Research Center (East Hartford, CT, USA)
Organization: United Technologies Research Center
Date: Thu, 11 Jan 1996 20:14:42 GMT
Associate Research Engineer
DUTIES AND RESPONSIBILITIES:
United Technologies Research Center (UTRC) is seeking an individual with
hands-on experience with Data Mining techniques for a position in the
Diagnostic Technology Group. The successful candidate will participate
in a Research and Development program focused on Knowledge Discovery in
diagnostic databases. The ability to analyze system requirements,
evaluate technology solutions, integrate existing diagnostic databases,
and apply data mining techniques to achieve measurable benefits to the
UTC operating units is required.
QUALIFICATIONS:
The successful candidate will have an advanced degree (Ph.D.) in
Computer Science with a background in Data Mining / Knowledge Discovery
in Databases and a strong database management background. Experience
with commercial Data Mining tools and database systems is a plus.
PREFERRED QUALIFICATIONS:
A broad background in Artificial Intelligence techniques, especially
Model-Based Reasoning and Knowledge-Based Systems, is desirable.
Knowledge of software engineering methodologies and strong programming
skills (Lisp, C++, Java) are a plus.
ADDITIONAL INFORMATION:
The Diagnostic Technology Group at UTRC is responsible for developing
innovative diagnostic capabilities and transferring them to the UTC
operating units. The successful candidate will join a team of
researchers applying signal processing, pattern recognition, and
artificial intelligence techniques to problems in embedded diagnostics,
remote monitoring, and maintenance aiding.
United Technologies Research Center offers a competitive salary and
benefits package designed to attract and retain talented
professionals. Send resume to: Professional Staffing Code 95-55,
MS129-35, United Technologies Research Center, 411 Silver Lane, East
Hartford, CT 06108 or E-mail to WWWEO@utrc.utc.com.
An equal opportunity
employer.
Theory and Practice of Object Systems (TAPOS)
=============================================
Editors in chief:
Karl Lieberherr, Northeastern University, Boston, Massachusetts
Roberto Zicari, Johann Wolfgang Goethe University, Frankfurt, Germany
**************
Aims and Scope
**************
Theory and Practice of Object Systems is an archival, peer reviewed
journal dedicated to publishing high quality research results. Papers will
be selected primarily in areas of Object Technology, including, but not
limited to:
- Programming Languages and Models
- Foundations, Semantics, Type Theory
- Database Management Systems and Database Languages
- Concurrency
- Distribution
- Software Engineering and Software Development Tools and Environments
- Formal Specification
- Metrics and Evaluation
- Analysis and Design Methods
- Novel Applications
- Operating Systems
Contributions in other areas of object-based computing are also
welcome.
Research contributions on these aspects
will be collected under the interdisciplinary umbrella of the object-oriented
approach they have in common rather than from the point of view of the
parent discipline.
Theoretical papers should either break significant new ground or
unify and extend existing theories.
Systems papers should emphasize the underlying principles and
important discoveries, backed up by architectural and
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Published quarterly, Theory and Practice of Object Systems (TAPOS)
disseminates new, but long
lasting concepts and results of high quality useful to researchers and
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The main goal of TAPOS is to
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The journal is a service to the object community in that it provides
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*********************
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*********************
The editors-in-chief encourage the submission of contributions from all
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should be sent to one of the editors-in-chief.
The editors-in-chief will assign the article to an Associate
Editor whose subject area expertise is appropriate to the
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Published papers will include the name of the Associate Editor
who managed the refereeing process.
A special transfer of copyright agreement, signed and executed by the
author, must be provided when an article is accepted. (If the article
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Copies of the copyright agreement may be obtained from the editors-in-chief
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Please submit your paper to either of the following addresses:
Professor Karl Lieberherr
Editor, TAPOS
Northeastern University
College of Computer Science
125 Cullinane Hall
Boston, MA 02115-9959
U.S.A.
lieber@CCS.neu.EDU
Professor Roberto Zicari
Editor, TAPOS
Johann Wolfgang Goethe-Universitaet
Fachbereich Informatik (20)
Robert Mayer Strasse 11-15
D-60325 Frankfurt am Main, Germany
zicari@informatik.uni-frankfurt.de
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E-mail: RO'Hanley@jwiley.com
Professor TSE Maibaum
Head, Department of Computing
Imperial College of Science Technology and Medicine
180 Queen's Gate
London SW7 2BZ
UK
Areas:
formal methods, specification and
implementation, concurrency and real time, modularisation.
-----------------------------------------------------------
Dr. Jose Meseguer
Computer Science Laboratory
SRI International
333 Ravenswood Avenue
Menlo Park, CA 94025, USA
Areas:
mathematical foundations of OOP, formal specification of OO systems,
declarative approaches to concurrent OOP
-----------------------------------------------------------
Professor Atsushi Ohori
Research Institute for Mathematical Sciences
Kyoto University
Sakyo-ku, Kyoto 606-01
Japan
Areas:
type systems
data models
database programming language
-----------------------------------------------------------
Dr. Harold Ossher, H1-B26
IBM T. J. Watson Research Center
P. O. Box 704
Yorktown Heights, NY 10598
Areas:
software composition
system structure
software development environments
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-----------------------------------------------------------
Dr. Remo Pareschi
Rank Xerox Research Centre
6, chemin de Maupertuis
F-38240 Meylan
France
Professor Michael I. Schwartzbach
Computer Science Department
Aarhus University
Ny Munkegade
DK-8000 Aarhus C
Denmark
Areas:
type systems, semantics, theory, implementation.
-----------------------------------------------------------
Professor Mario Tokoro
Department of Computer Science
Keio University
3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223 Japan
Areas:
Concurrent and Distributed Computation Models, Programming Languages,
Operating Systems, and MultiAgent Systems.
-----------------------------------------------------------
Professor Akinori Yonezawa
Dept. of Information Science
Faculty of Science
University of Tokyo
Hongo, Bunkyo-ku
Tokyo 113 Japan
Areas:
concurrency, algorithms, language design, language implementation.
-----------------------------------------------------------
Editorial board:
Serge Abiteboul, INRIA, Paris, France
Elisa Bertino, University of Milano, Milano, Italy
Kim Bruce, Williams College, Williamstown, MA
Luca Cardelli, Digital, Systems Research Center, Palo Alto, CA
Bjorn Freeman-Benson, Carleton University, Ottawa Canada
Narain Gehani, AT&T Bell Labs, Murray Hill, NJ
Carlo Ghezzi, Politecnico di Milano, Milano, Italy
Juerg Gutknecht, Swiss Federal Institute of Technology, Zurich, Switzerland
Roger King, University of Colorado, Boulder, CO
Kai Koskimies, University of Tampere, Tampere, Finland
Barbara Liskov, Massachusetts Institute of Technology, Cambridge, MA
Dino Mandrioli, Politecnico di Milano, Milano, Italy
John Mitchell, Stanford University, Palo Alto, CA
Jens Palsberg, Northeastern University, Boston, MA
Hamid Pirahesh, IBM Almaden, Almaden, CA
John Reif, Duke University, Durham, NC
Andreas Reuter, University of Stuttgart, Stuttgart, Germany
Marc Scholl, University of Ulm, Ulm, Germany
Richard Soley, Object Management Group, Framingham, MA
Stanley Zdonik, Brown University, Providence, RI
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Previous8NextTop
>~~~Meetings:~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
From: Blaz.Zupan@ijs.si
(Blaz Zupan)
Subject: CFP: ECAI96 WS Intelligent Data Analysis in Medicine and Pharmacology
Date: Fri, 12 Jan 1996 11:18:00 +0100 (MET)
INTELLIGENT DATA ANALYSIS IN MEDICINE AND PHARMACOLOGY
(IDAMAP-96)
First Call for Papers for the Workshop at
ECAI-96
12th European Conference on Artificial Intelligence
August 12-16, 1996
Budapest, Hungary
Organized by:
Nada Lavrac, J. Stefan Institute, Slovenia (chair)
Pedro Barahona, Universidade Nova de Lisboa, Portugal
Riccardo Bellazzi, University of Pavia, Italy
Werner Horn, Austrian Research Institute for Artificial Intelligence
Elpida Keravnou, University of Cyprus (co-chair)
Cristiana Larizza, University of Pavia, Italy
Blaz Zupan, J. Stefan Institute, Slovenia (co-chair)
GENERAL INFORMATION
IDAMAP-96, an ECAI-96 workshop, will be held in Budapest, Hungary, on
12 or 13 August 1996, immediately before the main ECAI-96 conference,
August 14-16, 1996. The workshop will last one full day.
Gathering in an informal setting, workshop participants will have the
opportunity to meet and discuss selected technical topics in an
atmosphere which fosters the active exchange of ideas among
researchers and practitioners. To encourage interaction and a broad
exchange of ideas, the workshop will be kept small, preferably around
30 participants.
TOPIC
The gap between data generation and data comprehension is widening in
all fields of human activity. In medicine and pharmacology overcoming
this gap is particularly crucial since medical decision making needs
to be supported by arguments based on basic medical and pharmacologi-
cal knowledge as well as knowledge, regularities and trends extracted
from data by intelligent data analysis techniques.
The topic of the workshop are computational methods for intelligent
data analysis aimed at narrowing the gap between data gathering and
data comprehension, as well as their applications in medicine and
pharmacology.
Topics include, but are not limited to, effective machine learning
tools, clustering, data visualization, interpretation of time-ordered
data (derivation and revision of temporal trends and other forms of
temporal data abstraction), learning with case bases, discovery of new
diseases, new drug compounds, pharmacodynamical modelling, predicting
drug activity, etc. Emphasis will also be given to solving of problems
which result from automated data collection in modern hospitals, such
as analysis of computer-based patient records (CPR), analysis of data
from patient-data management system (PDMS), intelligent alarming,
effective and efficient monitoring, etc.
SCIENTIFIC PROGRAM
The scientific program of the workshop will consist of presentations
of accepted papers and panel discussions.
Papers are invited both on methodological issues of data mining as
well as on specific applications in medicine and pharmacology. The
preferred length of papers is 10 pages.
Panel discussions will consist of commentators' views on the presented
papers as well as on discussions initialized by participants. In order
to be able to organize these discussions, entries for discussions are
encouraged on any topic related to the workshop. We especially
encourage entries on the topic 'Data mining and knowledge discovery -
its practical potential in medicine and pharmacology'. The preferred
length of entries for panel discussions is 1 page.
SUBMISSION OF PAPERS
Submit papers (preferably 5 hard copies, 8-12 pages, possibly
postscript) and panel discussion entries (hardcopy or electronic,
1 page) to:
Nada Lavrac, Blaz Zupan
J. Stefan Institute
Jamova 39
61000 Ljubljana
Slovenia
tel. +386 61 177 3272, 177 3380
fax. +386 61 125 1038, 219 385
email: ecai96wk@ijs.si
Submissions must include first author's complete contact information,
including address, email, phone and fax.
WORKSHOP PARTICIPATION
Workshop participation is not limited to authors of submissions. A
limited number of other attendees will be selected based on submitted
statements of interest for participation at the workshop. A statement
of interest (send an email to ecai96wk@ijs.si)
should include the name,
address, email, phone, fax and description of research interest.
IMPORTANT DATES
- Paper submission deadline April 2, 1996
- Notification to Authors April 26, 1996
- Camera-ready papers May 15, 1996
PUBLICATION OF PAPERS
Accepted papers will be published in ECAI-96 working notes. It is
planned to published a post-conference publication based on selected
workshop papers.
WORKSHOP FEE
- Workshop fee is 50 ECU per participant.
- Attendees at workshops must register also for the main ECAI
conference.
Previous9NextTop
>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Date: Sun, 14 Jan 96 14:39:39 EST
From: iimam@aic.gmu.edu
(Ibrahim Fahmi Imam)
Subject: CFP: AAAI-96 WS on Intelligent Adaptive Agents
C A L L F O R P A P E R S
AA AA AA IIII IIII AA AA
AAAA AAAA AAAA II II AAAA AAAA
AA AA AA AA AA AA II __ II AA AA AA AA
AAAAAAAA AAAAAAAA AAAAAAAA II __ II AAAAAAAA AAAAAAAA
AA AA AA AA AA AA II II AA AA AA AA
AA AA AA AA AA AA IIII IIII AA AA AA AA
AAAI-96 International Workshop on
Intelligent Adaptive Agents (IAA-96)
August 4-8, 1996, Portland, Oregon
In recent years, researchers from different fields have pushed toward greater flexibility and intelligent adaptation in their systems. The development of intelligent adaptive agents has been rapidly evolving in many fields of science. Such systems should have the capability of dynamically adapting their parameters, improve their knowledge-base or method of operation in order to accomplish a set of tasks. This workshop will focus on intelligent adaptation and its relationship to other fields of interest.
Research issues that are of interest to the workshop include but are not limited to:
1) Analyzing the role of adaptation in planning, execution monitoring, and
problem-solving;
2) Adaptive control in real-world engineering systems;
3) Analyzing the computational cost of adaptation vs. system robustness;
4) Controlling the adaptive process (what is the strategy? what is needed?, what is expected?, etc.);
5) Adaptive mechanisms in an open agent society;
6) Adaptation in distributed systems;
The workshop seeks high quality submission in these areas. Researchers interested in submitting papers should explain the adaptive process in light of one or more of the issues presented above. Papers with real-world applications are strongly encouraged.
Please send any questions to: Ibrahim F. Imam at
iimam@aic.gmu.edu
Program Committee Members
Gerald DeJong, University of Illinois at Urbana-Champaign, USA
Tim Finin, University of Maryland Baltimore County, USA
Brian Gaines, University of Calgary, Canada
Diana Gordon, Naval Research Laboratory, USA
Yves Kodratoff, Universite de Paris Sud, France
Ryszard Michalski, George Mason University, USA
Ashwin Ram, Georgia Institute of Technology, USA
Nigel Shadbolt, University of Nottingham, England
Reid Simmons, Carnegie Mellon University, USA
Walter Van de Velde, Vrije Universiteit Brussel, Belgium
Brad Whitehall, United Technologies Research Center, USA
Stefan Wrobel, GMD, Germany
Submission Information
Paper submissions should not exceed eight single-spaced pages, with 1 inch
margins, 12pt font. The first page must show the title, authors' names, full surface mail addresses, fax number (if possible), email addresses, short
abstract (does not exceed 200 words), and a list of key words (up to 5).
Electronic submissions are strongly encouraged and should be sent to the updated email address specified in the workshop World-Wide Web page. Otherwise, contact the workshop chair at (iimam@aic.gmu.edu)
for mailing arrangements. An extended version of the CFP can be found in:
Submission Deadline: March 18, 1996
Notification Date: April 15, 1996
Camera-Ready Due: May 13, 1996
Workshop: August 4, 1996
The workshop is a one day workshop.
Previous10NextTop
>~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Return-Path: (gps0@ns.gte.com)
Date: Mon, 15 Jan 1996 14:15:15 -0500 (EST)
From: Russell Greiner (greiner@scr.siemens.com)
To: kdd@gte.com
Subject: CFP: Relevance in Knowledge Representation and Reasoning
Content-Type: text
Content-Length: 5147
Essentially all reasoning systems use a corpus of information to reach
appropriate conclusions. For example, deductive systems use initial
theories (possibly encoded as predicate calculus statements) from
which they draw conclusions, probabilistic systems use prior
distributions (possibly encoded as a Bayesian network) to compute
event probabilities, and abductive processes produce explanations
based on both background theories and observations.
With too little information, these systems clearly cannot work
correctly. Surprisingly, too *much* information is also problematic,
as it too can cause significant degradation in system performance. It
is therefore critical to determine what information is irrelevant, to
know what can be ignored or downplayed when considering a specific
task (e.g., a specific query, or distribution of queries, to the
system, or a specific observation to be explained). In some cases,
ignoring irrelevant information is needed in order to draw the correct
conclusions.
There are many forms of irrelevance. In some contexts, the initial
theory may include more information than the task requires, or
information at a level of granularity that is more detailed than
necessary. Here, the system may perform more effectively if it
ignores or deletes certain irrelevant facts or if it ignores certain
distinctions made in the representation. Another flavor of
irrelevance arises during the course of reasoning: A reasoning process
can ignore certain intermediate results, once it has established that
they will not contribute to the eventual answer.
This workshop follows the very eclectic 1994 Relevance Symposium,
which investigated the notion of relevance across various fields of
Artificial Intelligence and Computer Science. The current workshop,
however, will focus on the use of relevance in knowledge
representation and reasoning, specifically, on understanding different
forms of irrelevance, and exploiting this 'relevance information' to
improve the performance of reasoning systems. Submissions are
requested in areas relating to relevance in KR&R, including, but not
limited to, the following:
o Speeding up inference using relevance reasoning.
o Relevance in probabilistic reasoning.
o Relevance in explanation.
o Relationships between relevance and belief revision and updates.
o Relevance reasoning as a basis for abstraction and reformulation.
o Using relevance of information to enable drawing appropriate
conclusions.
o Applications of relevance reasoning.
o Reasoning about relevance of information, and foundations of
relevance reasoning.
Submission Information
======================
Authors wishing to present a paper should submit an extended abstract
of at most 5000 words. Accepted participants will be invited to
submit full papers for the workshop proceedings, which will be
distributed to the workshop participants. Persons wishing to attend
the workshop and not to present papers should submit a 1--2 page
research summary that includes a list of relevant publications.
Authors are encouraged to submit PostScript versions of their paper by
email to either Russ Greiner (greiner@scr.siemens.com)
or Alon Levy
(levy@research.att.com).
Authors unable to submit by email should send
4 copies of their paper to the address below. All submissions should be
received by July 8, 1996. Please be sure
to include e-mail address, telephone number and mailing address of
the principal author. In case of multiple authors, please indicate
which authors wish to participate. Notification of acceptance or
rejection will be mailed to the principal author by August 16, 1996.
Camera-ready copies of papers accepted for inclusion in the
proceedings will be due September 17, 1996.
Address for hardcopy submissions:
Russell Greiner
Siemens Corporate Research, Inc
755 College Road East
Princeton, NJ 08540-6632
Important Dates
===============
- Submissions due: July 8, 1996.
- Notification of acceptance August 16, 1996.
- Final version due September 17, 1996.
- Workshop dates November 3-4, 1996.
Program Chairs:
===============
Russ Greiner (Siemens Corporate Research, greiner@scr.siemens.com)
Alon Levy (AT&T Bell Laboratories, levy@research.att.com)
Program Committee:
==================
Adnan Darwiche (Rockwell)
Jim Delgrande (Simon Frasier University)
Daphne Koller (Stanford University)
Gerhard Lakemeyer (University of Bonn)
Alberto Mendelzon (University of Toronto)
Devika Subramanian (Rice University)
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