*
Davide Roverso, Norway: Research Positions at STO Meetings: *
Bill Goodin, UCLA short course on 'Data Mining Techniques and
Applications', Feb 2-5, 1998 *
Gordianknot, Courses on Data Mining and Analysis of Financial Markets *
Thrun, Conference on Automated Learning and Discovery,
Pittsburgh, PA, June 11-13, 1998,
--
Data Mining and Knowledge Discovery community, focusing on the
latest research and applications.
Submissions are most welcome and should be emailed to gps.
Submissions should have a descriptive subject line and a relevant
web address for more information. Submissions, especially meeting
announcements, may be edited for space.
KD Nuggets frequency is 2-3 times a month.
Back issues of KD Nuggets, a catalog of data mining tools
('Siftware'), pointers to Data Mining Companies, Relevant Websites,
Meetings, and more is available at Knowledge Discovery Mine site
at
********************* Official disclaimer ***************************
All opinions expressed herein are those of the contributors and not
necessarily of their respective employers (or of KD Nuggets)
*********************************************************************
~~~~~~~~~~~~ Quotable Quote ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
A statistician and a lay person are about to be shot.
The executioner grants each one last request. The statistician
says 'I'd really like to give one last lecture on statistics.'
The lay person then asks to be shot first.
from Rob Tibshirani's lecture notes
'Some thoughts from half a career in statistics'
contributed by George H. John Previous1NextTop
From: Sal Stolfo (sal@cs.columbia.edu)
To: Fuey S Chong (F.S.Chong-ACS97@cs.bham.ac.uk),
gps
Subject: 'Agent' based data-mining
Phyllis
Regarding your kdnuggets posting, please go to the URL
where you will find details on our 'java-based' agent data mining
system. In fact, you can download our source code and install a ready to use
distributed/agent-based data mining facility NOW!
IBM's Intelligent Miner Wins the DM Review Readership Award: More than
200 readers surveyed by DM Review voted Intelligent Miner the best data
mining tool in the industry. 44% of the data professionals surveyed,
rated Intelligent Miner either an 'excellent' or a 'very good' product.
The runner up was rated 'excellent' or 'very good' by only 33%.
The IBM Intelligent Miner is a knowledge discovery toolkit for analyzing,
extracting and validating data traditionally held in data warehouses.
It consists of powerful algorithms and processing techniques that enable
users to analyze data stored in flat files or in enterprise databases such
as IBM DB2 Universal Database.
Previous3NextTop
Date: Tue, 11 Nov 1997 21:18:37 +1100
From: Data-Miner Software Kit (announce@data-miner.com)
Subject: Book Announcement: Predictive Data-Mining: A Practical Guide (WITH SOFTWARE)
Predictive Data-Mining: A Practical Guide (WITH SOFTWARE)
Sholom M. Weiss and Nitin Indurkhya
Morgan Kaufmann Publishers, San Francisco
August 1997; 225 pages; softcover; ISBN 1-55860-403-0; Price: 39.95 US
dollars.
Software Price: 24.95 US dollars.
FROM BACK COVER
---------------
As storage and retrieval technology has advanced to the point where the main
goals of classical databases - those of instant data recording and extremely
rapid responses to queries - are well within reach, and as the amount of data
stored in existing information systems has mushroomed, a new set of
objectives for data management has emerged. Very large collections of
data - millions or even hundreds of millions of individual records - are now
being compiled into centralized data warehouses and reorganized globally by
topic, allowing analysts to make use of powerful statistical and machine
learning methods to examine data more comprehensively. Searches using these
methods can be much more open-ended than traditional database queries, and,
while consuming more time and processing resources, can be expected to
return statistically valid results capable of showing trends and patterns
over time and providing a platform for forecasting future developments.
Data mining is the art and science of performing these massive,
open-ended analyses, and, most importantly, of extracting, transforming, and
organizing enormous quantities of raw data to facilitate a high-dimensional
search for predictive solutions. This book presents a unified view of the
field, drawing from statistics, machine learning, and databases and focusing
on the preparation of data and the development of an overall problem-solving
strategy. In addition, the authors review statistical and machine learning
search methods and, employing several real-life case studies, discuss the
hurdles encountered when applying these methods to real-world data warehouses
with all of their inescapable flaws and variances. A software option for
a state-of-the-art data mining kit enables the reader to apply the concepts
presented in the book. Anyone owning, building, or thinking of building a data
warehouse will find this book excellent preparation for the technical and
intellectual challenges associated with putting big data to work.
CONTENTS
--------
What is Data Mining?
Statistical Evaluation of Big Data
Preparing the Data
Data Reduction
Looking for Solutions
What's Best for Data Reduction and Mining
Art Or Science? Case Studies in Data Mining
SOFTWARE OPTION
---------------
DMSK (Data-Miner Software Kit) is a comprehensive collection of programs
for efficient mining of big data. It runs under Unix, Windows 95/NT or Java.
Both classical methods and more computationally expensive state-of-the-art
prediction methods are included. The software kit implements the
data-mining techniques presented in the book.
Previous4NextTop
[The following is a commercial announcement. GPS]
From: dg@mitgmbh.de
(Dagmar Gerigk)
Subject: DataEngine 2.1 - NEW SOFTWARE DIMENSION FOR DATA ANALYSIS
Date: 03 Nov 97 17:24:28 UT
By the end of November 1997 the new version of THE software tool for
data analysis, DataEngine 2.1, will be released by MIT- Management of
Intelligent Technologies (company profile see below).
General description of DataEngine:
- It is an efficient tool for technical and management applications.
- DataEngine extracts information from a large multitude of data using
fuzzy technologies, neural networks and statistical methods.
- Applications with the previous version were successfully realized in
the fields of: quality control, process analysis, forecasting, data
base marketing and diagnosis.
- DataEngine helps among others to maintain a high quality standard,
to reduce production costs, to realize better production planning by
more precise forecasts and to direct marketing activities carefully.
- Its 32 bit architecture, a powerful data visualisation component and
an easy operation of the user interface provide lots of conveniences
for the user.
- DataEngine 2.1 was developed for Windows 95 and Windows NT.
Innovations compared to the previous version:
- Due to its interfaces to other programs DataEngine can be flexibly
integrated into the user's working environment.
- Data can be accessed by the import and export of ASCII or MS-
Excel files as well as by the ODBC interface.
- DataEngine 2.1 can be extended by PlugIns, so called user defined
function blocks, such as e.g. PlugIns for automatic feature
selection or for accessing data acquisition hardware.
The main innovations at a glance:
- ODBC -interface
- ASCII export and MS-Excel export
- increase in speed
- online help
- multi threading (support of multiprocessor
systems)
For further information (e.g. price list, detailed
technical descriptions, update conditions, information on PlugIns)
please contact us at:
MIT-Management of Intelligent Technologies
Promenade 9
52076 Aachen
Germany
Tel: +49-2408-94580
Fax: +49-2408-94582
WWW:
To get a first impression of DataEngine 2.1 ask for a free demo.
Company Profile:
MIT is one of the leading companies for Intelligent Technologies such
as Fuzzy Logic and Neural Networks. Its main tasks consist of advisory
service, planning and realization of projects in the following fields:
acoustic and optical quality control,
image processing,
process analysis,
forecasting,
medical and technical diagnosis,
production planning and control.
MIT applies its own products as well as those of other producers to
realize efficient systems for management and production tasks. MIT
solutions are applied in industry (e.g. glass, chemical, steel and
automotive) as well as in other areas (Finance and Trading).
MIT also offers training courses and feasibility studies which show
the potential for efficient data analysis or production planning in
the customer's special area. This guarantees a decision support
without being obliged to invest much money.
Besides this MIT offers an intensive technology transfer and
international activities. MIT organizes various symposia and
conferences on Intelligent Technologies (among others EUFIT - the
biggest European conference on Fuzzy Technologies and Neural
Networks). The close cooperation with the RWTH Aachen (Aachen
Institute of Technology) ensures an efficient transfer of new research
results. MIT is managing member of the Neuro-Fuzzy Initiative
North-Rhine-Westfalia and founding node of a Network of Excellence for
Fuzzy Logic. MIT has distributors worldwide and still searches for
more.
Previous5NextTop
Date: Mon, 10 Nov 97 12:15:22 +0100
From: Hugues Marty (hugues@isoftfr.isoft.fr)
Subject: Siftware: Alice 4.3
User action tracking
One click mining
Better user assistance
Advanced graphics within Decision Tree nodes
Four new reports for instant target selection
Direct access to SAS files
Raphaelle Thomas
International Development Manager
alice-news@isoft.fr
Previous6NextTop
Subject: Relevant Access to Text, Media, Markets--by Pidgin
Date: Tue, 11 Nov 97 23:09:19 PST
From: Stanley Rice (autospec@mail.cruzio.com)
A new 'MAJOR APPLICATION' is heading for the Internet.
DETAILED MATCHING OF DEMAND-PROFILES WITH SUPPLY-PROFILES.
Methods, basis, background, examples, fuzzy strategies, etc.
Anyone can play, free. (Nothing for sale.)
Cheers, Stan Rice
--
THEMATICS: Conceptual & Marketing Access to Text and Media
AUTOSPEC, Inc. Santa Cruz, CA. Stan Rice Voice: (408) 457-1430
E-mail: autospec@cruzio.com
WWW:
Previous7NextTop
From: markus@acsys.anu.edu.au
Date: Tue, 4 Nov 1997 12:43:20 +1100 (EST)
Subject: Australia: Research Positions, Expressions of Interest
Position: Researcher, Level A/B/C
Company: Cooperative Research Centre for Advanced Computational Systems
Geographic Location: Canberra, Australia
A number of vacancies exist for researchers interested in working at a
premier R&D centre using advanced computing facilities and infrastructure.
The ACSys CRC is based in Canberra with collaborating research groups in
Sydney, Adelaide and Perth, with an annual budget of over $8 million.
Over forty research and commercial organisations are involved in ACSys
activities. The central theme of ACSys is 'managing the information
explosion' and the Centre targets advanced information technologies in:
* highly interactive user interfaces * high performance computation
* large scale data management * broadband networks
ACSys is calling for Expressions of Interest from suitably qualified
researchers prior to proceeding to advertisement. Appointments will be
made at either Postdoctoral Fellow (Level A), Research Fellow (Level B)
or Fellow (Level C) or equivalent levels. Closing Date: 14 November 1997
More information:
Markus Buchhorn, Advanced Computational Systems CRC | Ph: +61 2 62798810
email: markus@acsys.anu.edu.au,
snail: ACSys, RSISE Bldg,|Fax: +61 2 62798602
Australian National University, Canberra 0200, Australia |Mobile: 0417 281429 Previous8NextTop
From: Davide Roverso (Davide@linn.sto.no)
Date: Mon, 10 Nov 1997 08:20:06 +0200
Subject: Norway: Research Positions at STO
STO
Oestfold Research Foundation (STO) is a Norwegian regional research
foundation established in 1988. STO is organized in three institutes,
Institute for Information Technology, Institute for Pollution Prevention,
and Institute for Local Government. STO has offices in Halden and
Fredrikstad, Norway and has about 55 employees.
HOW WOULD YOU LIKE TO WORK IN HALDEN, NORWAY, A CITY OF THRIVING
INFORMATION TECHNOLOGY AND ENVIRONMENTAL DEVELOPMENT?
A number of high tech research institutes and business companies have
helped to put Halden on the map as one of Norway's leading R&D
environments. Halden is the 3rd largest information technology centre
in Norway.
The city and its surroundings have a lot to offer in the way of nature
and open-air activities. Surrounding the city are large forests with
idyllic lakes. The archipelago of Hvaler and the Swedish West Coast
are also located within a short distance.
The city of Halden has a mixture of old and new residential areas
situated near the centre of the city. Property prices are reasonable
in Halden compared to those of the majority of Norwegian cities.
The Institute for Information Technology -(IFI) is located in Halden
and is a dynamic and international part of the regional and national
information techology environment.
IFI wishes to strengthen its competence in the following areas:
- Knowledge based systems
KBS in data mining, knowledge management and BPR
Expert systems
Neural networks
- Component Based Development
OOA/OOD/OOP, UML
CORBA, COM, DCOM, IIOP
Java, C++
- Database technology
RDBMS/OODBMS/OLAP/ROLAP,
Data Warehousing, Data Marts, Web Warehousing
and is seeking candidates at the Bachelor, Master or PhD level.
The work of the institute is based on research and development in both
private and public sectors. Our new personnel will be given
independent and challenging tasks in these areas.
We expect the applicants to have some experience from one or more of
the above mentioned areas as well as excellent written and spoken
communication skills in one of the Scandinavian languages or English.
Salary is negotiable, and it includes generous pension and
insurance schemes.
The workplace is Halden (alternatively Fredrikstad).
STO can assist regarding housing.
For more information, please contact Inger Ramstad, Davide Roverso or
Lars Solem.
email: inger@sto.no,
davide.roverso@sto.no,
lars@sto.no
Phone: +47 69 18 74 00
Fax: +47 69 18 74 14
Please forward your written application before 21.11.97
Previous9NextTop
From: 'Goodin, Bill' (bgoodin@unex.ucla.edu)
Subject: UCLA short course on 'Data Mining Techniques and Applications'
Date: Thu, 6 Nov 1997 17:43:17 -0800
On February 2-5, 1998, UCLA Extension will present the short course,
'Data Mining Techniques and Applications' on the UCLA campus in
Los Angeles.
The instructors are Wei-Min Shen, PhD, USC Information Sciences
Institute; Rakesh Agrawal, PhD, IBM Almaden Research Center; and
Jiawei Han, PhD, Simon Fraser University.
This course is intended for scientists, engineers, and information
managers who need to learn and apply data mining techniques (tools for
discovering valuable knowledge from very large data sets) to their
scientific research, system design, business management, or any other
related applications. The lecturers are among the world-leading
experts in the field with extensive experience in basic research as
well as in real industrial application.
This course should enable participants to understand and have hands-on
experience in:
o Basic concepts of data mining
o The overall process of data mining
o Critical steps in the data mining process
o Relationships between data mining and other scientific
disciplines
o Formalizing data mining problems
o Data preprocessing
o Data classification
o Data clustering
o Database structures and their operations
o Time serial data analysis
o Visualization
o Prediction and forecasting
The course fee is $1295, which includes extensive course materials.
These materials are for participants only, and are not for sale.
For additional information and a complete course description, please
contact Marcus Hennessy at:
This course may also be presented on-site at company locations.
----------------------------------------------------------------------
About the UCLA Short Courses (see www.unex.ucla.edu for details)
For more than 40 years, UCLA Extension has presented quality technical
and management short courses to a national and international
audience. These courses, which are three-to-five days in length, are
designed for engineers, managers, and others seeking to keep abreast
of new and rapidly changing technologies, as well as those wanting to
learn more about how to more effectively lead and manage people. The
instructors, who are recognized experts in their fields, are drawn
from academia, industry, and government and present a blend of theory
and practice. Nearly all of the 100 courses per year are held on the
UCLA campus in Los Angeles.
Previous10NextTop
Subject: Courses on Data Mining and Analysis of Financial Markets
From: agent@gordianknot.com
Date: Tue, 11 Nov 1997 15:16:10 -0500
Web:
The Gordian Institute will debut two new courses designed to introduce
corporate decision makers to data mining, and market timers to advanced
predictive technologies. The new seminars are designed to offer
intensive reviews of terminology, as well as benefits and pitfalls of
the technology while minimizing time away from the office. The data
mining course provides an optional third day hands-on workshop.
Details for both courses, to include specific dates, training sites and
detailed course outlines may be obtained through the contact
information provided at the end of this announcement.
'Data Mining: Principles and Practice' will host its initial offerings
in Santa Clara, CA in January, and Orlando, FL in February. At $995,
the two day data mining seminar covers the subject of data mining from
the ground up. Those in attendance will learn about different methods
of modeling and how those models apply to real business problems.
Those who desire to make data mining an integral part of their business
process are target candidates for Gordian's new offering. Attendees
will learn to:
- Uncover valuable information buried in data.
- Learn what data has real meaning and what data simply
takes up space (also known as 'data prospecting')
- Examine which data mining methods and tools are most effective
- Avoid pitfalls in the analysis of results
The rapid emergence of electronic data processing and collection
methods has lead some to call recent times as the 'Information Age.'
However, it may be more accurately termed as 'The Age of the Data
Glut.' Most businesses either posses a large database or have access
to one. These databases contain so much data that it becomes very
difficult to understand what that data is telling us. There is hardly
a transaction that does not generate a computer record somewhere.
All this data has meaning with respect to better understanding customer
needs and preferences. But how do you discover those needs and
preferences in a database that contains gigabits of seemingly
incomprehensible numbers and facts. Data mining does just that.
However, used blindly, incorporation of data mining techniques can
result in large expenditures of money and time to no avail. The key
issue explored in this seminar is how to avoid frustrating and costly
mistakes and improve your business process by correct use of these
powerful methods. Attendees will learn:
- The basic principles of data mining
- The different methods of data mining and how they compare
- How to prepare raw data for data mining
- How to analyze and validate the results
- What questions data mining can answer
- What are the pitfalls and how to avoid them
- What commercial products are available and how to evaluate them
Gordian's 'Data Mining: Principles and Practice' seminar focuses on
actual use and implementation of data mining techniques in the real
world. The instructor has been deeply involved with the development of
data mining methods and the means of their use. Actual products will
be reviewed, as will results drawn from real data mining applications.
Those who would like a hands-on perspective to the instructional
sessions may attend an optional third day application workshop for an
additional $495. The workshops will highlight superior performance as
well as pitfalls resulting from various tools and techniques when
applied to different types of data intensive problems. Exercises will
reveal impressive results from the same technique that may have failed
in another category.
In addition, objective evaluations of popular data mining products can
save immeasurable time and effort in assessing and selecting which
suite of tools will perform best for your application. The instructor
will show how to evaluate various packages based on strengths,
limitations, value and general performance. Products will be separated
into four categories:
- Statistical
- Decision Tree
- Neural Net
- Clustering Technologies
The presenter, Ben A. Hitt, Ph.D. has many years of experience using
pattern recognition technologies and intelligent software tools to
solve business problems. He has taught thousands of students in the
use and principles of advanced software and machine learning
technologies. He was Director of Training for NeuralWare, Inc. in
Pittsburgh, PA, and in that role instructed the use of neural networks
for Financial Forecasting, Fraud Detection, Process Control and Direct
Marketing. He was instrumental in the design and development of
ModelMAX, a complete neural network application for the direct
marketing industry. Dr. Hitt also designed and implemented a
nationally recognized detection system for rapid tax refund application
fraud. He has recently conducted a detailed and exhaustive survey of
commercial data mining products for a major US bank.
The one-day seminar 'Advanced Techniques for the Analysis of Financial
Markets' provides attendees with a methodology for developing a trading
strategy for financial instruments. The course addresses the selection
of financial instruments to monitor, establishing performance
objectives, and techniques for the development of a 'library' of
trading scenarios. This course will debut at $995 in Washington, DC in
January.
'Advanced Techniques for the Analysis of Financial Markets' is intended
for those who seek better than average performance from their
investment decision making. It is designed for the individual ready
and willing to explore approaches that have the potential to
dramatically out perform the market averages.
Recent research has proven that the financial markets are driven as
much by buyer behavior as by pure economics. This course abandons the
ideas behind capital market theory, portfolio theory and random walk.
In their place, we develop methods of identifying cases where
significant profit potential exists while screening out mediocre
performance.
The methods employed are geared toward individuals who trade financial
instruments for profit, not to 'own a good company.' The techniques
are most applicable to short-term and intermediate-term trading.
'Advanced Techniques for the Analysis of Financial Markets' focuses on
the development and implementation of techniques that can be directly
applied to trading financial instruments in a manner consistent with
the attendees goals and objectives. The instructor presents a
development methodology that allows attendees to identify trading
opportunities with a high probability of success.
The presenter, Thomas A. 'Tony' Rathburn left his teaching and research
position at Kent State University in 1992 to co-develop the course
Applying Neural Computing to Market Timing for NeuralWare, Inc. He is
the author of numerous publications and has extensive consulting
experience in the application of advanced analysis technologies to the
financial sector. Mr. Rathburn currently provides consulting services
to a variety of organizations on the application of advanced
technologies.
Reserve your seat early, as course sizes are limited to allow for a high
level of interaction with the instructors. Additional details for
Gordian's Data Mining or Financial Markets courses, to include course
outlines, specific dates, training sites and registration information may
be obtained through any of the following:
- Email: agent@gordianknot.com
(Send a message with any of the following as the SUBJECT)
- Data Mining Details
- Financial Markets Details
- Quarterly Newsletter
- Web:
Previous11NextTop
Subject: Conference on Automated Learning and Discovery
Date: Tue, 4 Nov 97 12:32:16 EST
From: thrun+@heaven.learning.cs.cmu.edu
Web:
The Conference on Automated Learning and Discovery will bring together
leading researchers from various scientific disciplines concerned with
learning from data. It will cover scientific research at the
intersection of statistics, computer science, artificial intelligence,
databases, social sciences and language technologies. The goal of
this meeting is to explore new, unified research directions in this
cross-disciplinary field.
The conference features eight one-day cross-disciplinary workshops,
interleaved with seven invited plenary talks by well-known
statisticians, computer scientists, and cognitive scientists. The
workshops will address issues such as: what is the state of the art,
what can we do and what is missing? what are promising research
directions? what are the most promising opportunities for
cross-disciplinary research?
* Visual Methods for the Study of Massive Data Sets
organized by Bill Eddy and Steve Eick
* Learning Causal Bayesian Networks
organized by Richard Scheines and Larry Wasserman
* Discovery in Natural and Social Science
organized by Raul Valdes-Perez
* Mixed-Media Databases
organized by Christos Faloutsos, Alex Hauptmann
and Michael Witbrock
* Learning from Text and the Web
organized by Jaime Carbonell, Steve Fienberg,
Tom Mitchell and Yi-Ming Yang
* Robot Exploration and Learning
organized by Howie Choset, Maja Mataric
and Sebastian Thrun
* Machine Learning and Reinforcement Learning for
Manufacturing
organized by Sridhar Mahadevan and Andrew Moore
* Large-Scale Consumer Databases
organized by Mike Meyer, Teddy Seidenfeld
and Kannan Srinivasan
For submission instructions, consult our Web page or contact the
organizers of the specific workshop. A limited number of travel
stipends will be available. The conference will be sponsored by CMU's
newly created Center for Automated Learning and Discovery.
Previous12NextTop
Date: Wed, 29 Oct 1997 17:49:27 +0000
From: Serafin Moral (smc@decsai.ugr.es)
Subject: UAI'98 Announcement
Web:
The 1998 UAI Conference will be co-located with ICML-98 (International
Conference on Machine Learning) and COLT-98 (Computational Learning
Theory). Registrants to any of the three conferences will be allowed
to attend without additional costs the technical sessions of the other
conferences. Joint invited speakers, poster sessions and a panel session
are planned for the three conferences.
The day after the co-located conferences (Monday, July 27, 1998), full day
workshops and/or tutorials will be offered by each of ICML, COLT, and UAI.
UAI will offer a full day course in which an overview of the field of
uncertain reasoning will be presented by a faculty of its distinguished
researchers. The AAAI-98 conference technical program begins on Tuesday,
July 28th.
UAI-98 will meet at the University of Wisconsin Business School, in close
proximity to the Convention Center, where AAAI-98 will be held.
* * *
CALL FOR PAPERS
Uncertainty management in artificial intelligence has now been established
as a well founded discipline, with a degree of development that has allowed
the construction of practical applications that are able to solve difficult
AI problems. Since 1985, the Conference on Uncertainty in Artificial
Intelligence (UAI) has served as the central meeting on advances in methods
for reasoning under uncertainty in computer-based systems. The conference
is a primary international forum for exchanging results on the use of
principled uncertain-reasoning methods, and it has helped the scientific
community move along the path from theoretical foundations, to efficient
algorithms, to successful applications. The UAI Proceedings have become a
basic reference for researches and practitioners who want to know about
both theoretical advances and the latest applied developments in the field.
We are very pleased to announce that UAI-98 will be co-located with ICML-98
(International Conference in Machine Learning) and COLT-98 (Computational
Learning Theory). This will be an outstanding opportunity for members of
the three communities to share ideas and techniques.
The scope of UAI covers a broad spectrum of approaches to automated
reasoning and decision making under uncertainty. Contributions to the
proceedings address topics that advance theoretical principles or provide
insights through empirical study of applications. Interests include
quantitative and qualitative approaches, and traditional as well as
alternative paradigms of uncertain reasoning.
We encourage the submission of papers proposing new methodologies and tools
for model construction, representation, learning, inference and
experimental validation. Innovative ways to increase the expressive power
and the applicability spectrum of existing methods is encouraged as well;
hybrid approaches may, for example, provide one way to achieve these goals.
Papers are welcome that present new applications of uncertain reasoning
that stress the methodological aspects of their construction and use.
Highlighting difficulties in existing procedures and pointing at the
necessary advances in foundations and algorithms is considered an important
role of presentations of applied research.
Knowledge Discovery Nuggets Index