(text)
Giorgos Paliouras, Call for Workshops, ACAI-99 machine learning school
(text)
Ibrahim Imam, Final CFP IEA/AIE-99 (Deadline OCT. 31)
Cairo, Egypt, May 31- June 3, 1999
--
newsletter focusing the latest news, publications, tools, meetings, and
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(thanks to http://www.geocities.com/Colosseum/3505/quotations.htm
Previous1NextTop
Date: Wed, 30 Sep 1998 08:57:55 -0500
From: Maria Zemankova mzemanko@nsf.gov
Subject: NSF Names New Director for CISE
Media contact: September 29, 1998
K. Lee Herring NSF PA 98-4
NSF NAMES NEW DIRECTOR OF
COMPUTER AND INFORMATION SCIENCE AND ENGINEERING
The National Science Foundation (NSF) has named University of
Pennsylvania computer science and engineering professor Ruzena
Bajcsy, Ph.D., to be Assistant Director for NSF's Computer and
Information Science and Engineering Directorate (CISE). Bajcsy
(pronounced 'buy chee') will assume her new position in December.
She will replace Juris Hartmanis, who will have completed his
term of service and return to Cornell University.
Bajcsy is a pioneering researcher in machine perception, robotics
and artificial intelligence. She is a professor both in the
Computer and Information Science Department and in the Mechanical
Engineering and Applied Mechanics Department and is a member of
the Neuroscience Institute in the School of Medicine. She is
also director of the university's General Robotics and Active
Sensory Perception Laboratory, which she founded in 1978.
Bajcsy has done seminal research in the areas of human-centered
computer control, cognitive science, robotics, computerized
radiological/medical image processing and artificial vision. She
is highly regarded not only for her significant research
contributions but also for her leadership in the creation of a
world-class robotics lab, recognized world wide as a premiere
research center. She is a member of the National Academy of
Engineering as well as the Institute of Medicine. Bajcsy is
especially known for her wide-ranging, broad outlook on the field
and cross-disciplinary talent and leadership, successfully
bridging such diverse areas as robotics and artificial
intelligence, engineering and cognitive science.
Bajcsy received her master's and Ph.D. degrees in electrical
engineering from Slovak Technical University in 1957 and 1967,
respectively. She received a Ph.D. in computer science in 1972
from Stanford University, and since that time has been teaching
and doing research at Penn's Department of Computer and
Information Science. She began as an assistant professor and
within 13 years became Chair of the department. Prior to the
University of Pennsylvania, she taught during the 1950s and 1960s
as an instructor and assistant professor in the Department of
Mathematics and Department of Computer Science at Slovak
Technical University in Bratislava. She has served as advisor to
more than 20 Ph.D. recipients.
As head of NSF's CISE directorate, Bajcsy will manage a budget of
approximately $300 million annually. Bajcsy is the sixth person
to be named to this position since the directorate was created in
1986. Her selection followed a national search chaired by
Stanford University Dean of Engineering John Hennessy.
I'm very interested in information about incremental data mining. Can you help
me? My name is Angilica, and I'm working on this as my project for
master's thesis.
Thank you.
Angélica Caro
( Other people will also be interested in information about incremental
data mining, so if you have such information, please respond to gps
and I will summarize to the KDnuggets readers. GPS)
Previous3NextTop
Date: Fri, 2 Oct 1998 17:16:36 -0400
From: Kurt Thearling KThearling@exapps.com
Subject: Keys to the Commercial Success of Data Mining
A web site collecting the papers and presentations from the KDD'98 workshop
'Keys to the Commercial Success of Data Mining' is now available on the web
at http://www.santafe.edu/~kurt/workshop.shtml.
This workshop brought
together a diverse group of developers, users, and integrators of business
data mining applications. Five formal presentations were combined with two
panel sessions a lot of discussion.
Summary:
Data mining is on the cusp of true commercial success. Commercial
institutions are starting to move beyond pilot studies and research programs
toward the production use of predictive models for real world business
applications. While this is exciting, it is also where it gets harder.
Successful data mining in business doesn't come down to simply having a hot
algorithm and giving it to an experienced modeler. Business users care about
things such as database support, application integration, business
templates, flexibility, scalability, real profitability, and other issues
that have not historically been the concern of the KDD community.
From a development point of view, the core algorithms are now a small part,
perhaps 10%, of the overall data mining application, which itself is only
10% of the business process that contains the application. This workshop
focused on the remaining 99% so that commercial data mining applications are
relevant to business users.
- kurt
Kurt Thearling
Director of Analytics
Exchange Applications
Previous5NextTop
Date: Fri, 9 Oct 1998 15:53:41 -0700 (PDT)
From: Hillol Kargupta hillol@eecs.wsu.edu
Subject: 'Advances in Distributed Data Mining' Book
CALL FOR PAPERS
for
'Advances in Distributed Data Mining' Book
Hillol Kargupta and Philip Chan
AAAI Press
A new book, entitled 'Advances in Distributed Data Mining', is expected
to be published in Spring of 2000 by AAAI Press. Distributed Data Mining
(DDM) deals with the data mining problem in an environment with distributed
data and computation. The objective of this book is to introduce the
readers to the field of DDM and to present the state of the art
developments in DDM research. Authors from the recently held Distributed
Data Mining Workshop http://www.eecs.wsu.edu/~hillol/kdd98ws.html
at the 1998 International Conference on Knowledge Discovery and Data
Mining are invited. Other leading DDM researchers are also expected to
contribute. In addition to these papers, we invite submissions of
papers in the following and other related areas:
1) Theory and foundation issues in DDM: Problem decomposability and
data distribution; complexity issues in DDM; representational issues.
2) Methods and algorithms: Distributed algorithms for popular data mining
techniques; techniques for communication minimization, cooperative
learning.
3) Software agents and DDM: Agent based approaches in DDM.
Agent interaction: cooperation, collaboration, negotiation,
organizational behavior, mobile agents.
4) DDM for spatial data: DDM in geographical information databases.
5) Architectural issues in DDM: Architecture, control, security,
communication issues.
6) Experimental DDM systems: Large experimental systems, performance,
design issues.
7) Applications of DDM: Application of DDM in business, science,
engineering, and medicine.
8) Human interaction in DDM: Human-DDM interface, multi-user interaction
in DDM.
9) Distributed data mining on the Internet.
11) Security Issues.
PAPER SUBMISSION:
All papers must be submitted to the following address:
Original submissions may be in Postscript, Word, pdf or HTML, as
well as hardcopy. Electronic submission is highly encouraged.
For hard-copy submission, please send five (5) copies of the full
paper to the above address. Final papers must be prepared in LaTeX
using the AAAI style files. Submissions should be in 12pt font,
1.5 line-spacing, and should not exceed 35 pages. All papers will
be subjected to the peer review process.
****************************************************************
If you are interested in submitting, please send the tentative
title and a brief abstract to hillol@eecs.wsu.edu
as soon as you
can. This will help us structuring the project and arranging the
reviewers. We strongly encourage you to do so by December 1, 1998.
****************************************************************
Postscript, pdf, and HTML files may be submitted using anonymous
ftp procedure, given below.
ftp ftp.eecs.wsu.edu
Name: anonymous
Password: YOUR E-MAIL ADDRESS
cd incoming/DDMBook
(to be available after October 1, 1998)
TIMETABLE:
Manuscript due: January 11, 1999
Notification of acceptance/rejection: February 10, 1999
Final version due: March 10, 1999
Book publication: Early Spring, 2000
Previous6NextTop
Date: Tue, 13 Oct 1998 10:58:22 -0500
From: Maria Zemankova mzemanko@nsf.gov
Subject: NSF POWRE Program, FAQ; proposals due 12/9/98
Frequently Asked Questions (FAQ) about the Professional Opportunities for
Women in Research and Education (POWRE) Program, is now available from the
NSF Online Document System (nsf98166) at:
POWRE Proposals Receipt Deadline: December 9, 1998, 5:00 p.m.
(Eastern Time for paper copies; local time for FastLane submission)
The official guidelines for submission of POWRE proposals can be
found in the Professional Opportunities for Women in Research and
Education (POWRE) program announcement (NSF 98-160), available
from the POWRE Web page. (From the NSF home page www.nsf.gov,
select 'Crosscutting Programs,' then 'POWRE.')
The questions and answers listed in FAQ are intended to be helpful supplements
to that document.
Previous7NextTop
Date: Thu, 15 Oct 1998 14:42:26 -1000 (HST)
From: James Widdoes seekjc@lava.net
Subject: Free Multiple Regression With Automatic Curve Fitting
If you do regression, least squares, or model building, then
is for you. It does 'automatic' curve fitting, for FREE.
It determines which variables to include in the model, what
transformations to make to each independent variable, if any,
what interaction terms to include in the model, both two way
and three way interaction terms, and what transformations
to make to those interaction terms, if any.
Please send your resume (or a pointer to it) to mhsu@hpl.hp.com
The data mining project within HP Labs is looking for an experienced,
energetic individual to head up the project.
Primary responsibility:
Managing ongoing research projects in data mining
techniques and applications, and information retrieval technologies.
Setting research directions, establishing and
furthering collaboration with existing and new
partners and customers, planning, leading and
participating in technical research activities.
Managing project resources, including people and budget.
Delivering results and fulfill commitments set in project plans.
Contribute to increasing the visibility of the Lab through
publications, patents, and presentations.
Required Qualifications:
Ph.D. in Computer Science or equivalent, specialized in
data mining and knowledge discovery and/or information
management technologies and applications. Minimum of 4
years of experience in the R&D function or equivalent.
Desired Qualifications
Strongly preferred: Experience in R&D management with a
track record in leading innovation and delivering results.
Also desired: Research experience in information retrieval,
database systems, artificial intelligence, distributed
systems, and/or Internet technologies.
Previous9NextTop
Date: Thu, 15 Oct 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
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
Previous10NextTop
Date: Tuesday, October 06, 1998 4:08 PM
From: Kerry Martin kerry@salford-systems.com
Subject: Data Mining with Decision Trees: Intro and Advanced CART Seminars
DATA MINING WITH DECISION TREES
* An Introduction to CART®
* CART® for Advanced Users
offered by Dan Steinberg, Salford Systems
INTRO COURSE DATES:
October 22-23, San Diego, CA
December 10-11, Syndey, Australia
ADVANCED COURSE DATES:
November 6, San Diego, CA
December 14, Syndey, Australia
AN INTRODUCTION TO CART. This popular two-day seminar is for business users
and IT audiences who are interested in understanding decision-tree
technology: what it is, why it works, how it has been used, and how it can
help you. On Day 1 learn about tree-structured data mining fundamentals
... about decision-tree applications ... how to build and interpret CART
trees ... and how to use advanced options for more accurate models. On
Day 2, put what you have learned to the test on your own data during a
hands-on CART session.
CART FOR ADVANCED USERS. Sharpen your decision-tree expertise during this
one-day advanced course for analysts and modelers with prior knowledge of
tree algorithms. Using case studies, seminar topics include: using CART
for exploratory data analyses, using alternative splitting rules,
conducting tree-stability analyses, manipulating priors, using bagging and
ARCing, and hybridizing CART with logistic regression, neural nets and MARS.
The Greater Boston Chapter of DAMA International - Mission Statement
The Greater Boston Chapter of the Data Administration Management
Association (DAMA) of DAMA International is a non-profit organization
that provides members with a forum for innovation in managing their
data as a corporate resource. In addition, DAMA provides an impetus
for advancement of the data administration field as an integral
business function in today's global and competitive
marketplace. Members of the Greater Boston Chapter of DAMA enjoy
benefits that include monthly speaker presentations on a wide range of
topics, discounts on books, and much more.
DAMA is organizing a one-day data warehousing and data mining conference
in Cambridge, MA, on Monday, November 30, 1998.
Keynotes:
Trends and Directions in Data Warehousing and Data Mining
Mitch Kramer, The Patricia Seybold Group
Challenges in Large-Scale Data Warehousing and Data Mining
Paul Barth, Tessera Enterprise Systems
Listen to experts from the Insurance, Banking, Financial Services,
High-Tech, and Consulting industry groups:
Track One Leveraging Today's Technology: Expanding the Data Warehouse
Explore the impact of effective design, enterprise
targeting, parallel architecture
Track Two Data Discovery and Analysis: Empowering the Organization
Examine the latest approaches to data mining strategies,
knowledge discovery in databases, geospatial analysis,
pattern management
Panel Discussion Data Quality - Partnership Between Business and IT
Share your experiences and interests with a panel of experts
Previous12NextTop
Date: Fri, 9 Oct 1998 10:33:14 +0300 (EET DST)
From: Giorgos Paliouras paliourg@iit.demokritos.gr
Subject: ACAI-99 machine learning school (abridged)
MACHINE LEARNING AND APPLICATIONS
Advanced Course on Artificial Intelligence 1999 (ACAI-99)
5-16 July 1999, Greece
* Preliminary Announcement (abridged) * http://www.iit.demokritos.gr/skel/eetn/acai99
The ECCAI Advanced Course on AI for 1999 (ACAI-99) is organised by the
Hellenic AI Society (EETN) on a Greek island. The goal of ACAI-99 is to
present the current state of the art in Machine Learning (ML), as well as to
show the potential of ML in a variety of problems. Towards this goal, the
course is structured as a multimodal event, containing plenary sessions from
distinguished lecturers, workshops on ML applications, student sessions and
panel discussions on the success of ML so far and its future directions.
ACAI-99 will be of benefit to professionals, who are interested in using
ML techniques, as well as researchers and postgraduate students, who work or
are thinking of working in this exciting field.
** List of plenary talks: **
T. Mitchell 'Machine learning: Setting the scene'
M. van Someren 'Machine learning and knowledge acquisition'
R. Michalski 'Concept learning'
Y. Kodrattoff 'Are ML applications a subfield of KDD?'
R.L. de Mantaras 'Case-based reasoning'
I. Bratko 'Noise handling in tree induction' &
'Inducing intermediate concepts'
P. Langley 'Machine discovery' &
'Formation of probabilistic concept hierarchies'
L. de Raedt 'ILP for data mining and machine learning'
N. Tishby 'A unified information theoretic approach to prediction,
clustering and learning'
C. Bishop 'Probabilistic graphical models'
J. Shapiro 'Genetic algorithms in artificial intelligence'
L. Saitta 'Multi-strategy learning'
** Important dates: **
October 30, 1998 Deadline: Submission of Workshop Proposals
December 1, 1998 Announcement: Selected Workshops
March 1, 1999 Deadline: Grant Applications & Student Papers
March 15, 1999 Announcement: Grant Offers & selected Student papers
April 1, 1999 Deadline: Workshop Programmes and Workshop Material
April 15, 1999 Deadline: Early Registration
June 15, 1999 Deadline: Late Registration
Previous13NextTop
Date: Fri, 9 Oct 1998 10:34:00 +0300 (EET DST)
From: Giorgos Paliouras paliourg@iit.demokritos.gr
Subject: Call for Workshops, ACAI-99 machine learning school
MACHINE LEARNING AND APPLICATIONS
Advanced Course on Artificial Intelligence 1999 (ACAI-99)
5-16 July 1999, Greece
* Call for Workshop Proposals (abridged)* http://www.iit.demokritos.gr/skel/eetn/acai99
The ECCAI Advanced Course on AI for 1999 (ACAI-99) is organised by the
Hellenic AI Society (EETN) on a Greek island. In the context of ACAI-99, we
plan to organise a series of Workshops on the application of Machine
Learning (ML) in a variety of problems. Each ACAI-99 Workshop will provide an
informal setting where Workshop participants will have the opportunity to meet
and discuss specific technical topics in an atmosphere which encourages the
active exchange of ideas among researchers and practitioners. Researchers from
all the segments of ML community are invited to submit Workshop Proposals for
review. Workshops will be held during the afternoon sessions of ACAI-99 and in
the period of 5-16 July.
** Requirements for Submission **
Proposals for Workshops should be between two and three pages in length,
and should contain the following information:
* A brief technical description of the Workshop.
* A brief discussion of why the Workshop is of interest.
* The names, addresses, phone numbers, and e-mail addresses of the
proposed Workshop organizing committee. This committee should consist
of at least two people knowledgeable in the technical issues to be
addressed by the Workshop.
* The name of one member of the organizing committee who is designated
as the primary contact.
* A list of Workshops previously arranged by any members of the proposed
organizing committee. Although previous experience with similar workshops
is not required, this would clearly be helpful.
* Estimation about the number of Workshop attendees, and, if possible a
list of potential attendees.
* A proposed schedule for organizing the Workshop and a preliminary agenda.
Proposers are encouraged to send their draft proposal to potential
participants for comments before submission.
** Important dates: **
October 30, 1998 Deadline: Submission of Workshop Proposals
December 1, 1998 Announcement: Selected Workshops
December 10, 1998 Calls for Participation to individual Workshops
April 1, 1999 Deadline: Workshop Programmes and Workshop Material
October 1, 1999 Deadline: Workshop reports
All proposals should be submitted by electronic mail, to vangelis@iit.demokritos.gr
in plain ASCII text.
IEA/AIE-99 continues the tradition of emphasizing applications of
artificial intelligence and expert/knowledge-based systems to
engineering and industrial problems. Topics of interest include, but
are not limited to:
Automated Problem Solving Intelligent Agents Natural Language Processing
Adaptive Control Intelligent Networks Neural Networks
CAD/CAM Intelligent Database Planning & Scheduling
Case-based Reasoning Intelligent Interfaces Practical Applications
Computer Vision Intelligent Tutoring Reasoning Under Uncertainty
Connectionist Models KBS Methodologies Robotics
Data Mining Knowledge Acquisition Sensor Fusion
Distributed AI Architect Knowledge Discovery Spatial & Temporal Reasoning
Expert Systems Knowledge Representation Speech Recognition
Fuzzy Logic Machine Learning System Integration Tools
Genetic Algorithms Model-based Reasoning Verification & Validation
Heuristic Searching
Authors are invited to submit 1) a URL address containing a printable
version of their paper; 2) a list of key words (some sample
topics are listed above); 3) no more than one page (by email)
describing: a) the contribution, b) the significance, and c)
the results of the presented work; and 4) one hard copy of
their paper to the Program Co-chair at the address given below
no later than October 31, 1998. Also, the conference will
contain a series of special track sessions. If an author
desires to include his/her paper in a special track, please
indicate that as well. A list of special tracks will be
announced through the URL: http://mason.gmu.edu/~iimam/ieaaie99/ieaaie99.html
For more information see the above URL.
Dr. Moonis Ali Dr. Ibrahim Imam
General Chair of IEA/AIE-99 Program Co-Chair of IEA/AIE-99
Southwest Texas State University Thinking Machines Corporation
Department of Computer Science 16 New England Executive Park
601 University Drive, Burlington, MA 01803, USA
San Marcos TX 78666-4616 USA Email: ifi@think.com
Email: ma04@swt.edu
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