Let me forward the call for papers for
the 4th international workshop on Chance Discovery.
Please deliver to your colleagus, and consider your own papers.
Yukio Ohsawa, Dr.
University of Tsukuba,
on behalf of the co-chairs
of The 4th International Workshop on Chance Discovery
*****
Call for Papers
4th International Workshop
on Chance Discovery:
From Data Interaction to Scenario Creation
http://technology.kingston.ac.uk/chanceDiscovery/CDWS/
August 11, 2005
University of Bonn,
Regina-Pacis-Weg 3, 53113 Bonn, Germany
We are pleased to invite submissions to the International Workshop on
Chance Discovery that will take place in Bonn, Germany, on August 11
as part of the International Conference on Machine Learning 2005.
(ICML2005: http://icml2005.ais.fraunhofer.de/home.php)
Brief description of the workshop content:
In a number of different areas, researchers in Artificial Intelligence
became recently interested in events or situations that affect human
decision making in that they are viewed as opportunities or risks.
A chance is such a rare event or a situation, which provides
opportunities or risks for human decision making or problem
solving. Noticing such an event is described as discovery of a
chance.
Therefore Chance Discovery can be characterized in terms of
- -- becoming aware of a chance and
- -- explaining its significance.
In this sense, the discovery of a chance is emphasized in contrast to
discovery by chance. The essential aspect of a chance is that it can
be the seed of new and significant changes in the near
future. Generally this means that being aware of a rare or novel
important event without ignoring it as noise is essential for future succe
ss.
A considerable part of the research in Chance Discovery can be
characterised in terms of interactions between computer-based and
human data interpretation. These interactions result in novel ideas,
which typically are expressed in the form of event sequences or
stories referred to as scenarios. Such scenarios have been proven to
be a useful tool for communicating novel ideas within an organisation.
The process of discovering a chance relies on various sub-areas of
Machine Learning, such as genetic algorithm research, neural net
research, reinforcement learning, meta-learning, discovery in
databases, conceptual clustering, inductive logic programming, and
others. It has been used in a variety of fielded applications in areas
such as management, marketing, medical diagnosis, earthquake forecast,
and product development.
Given these general characteristics, we intend to invite contributions
to all aspects of the process beginning with interactions between data
and leading to novel ideas in the form of scenarios. The review
process will equally consider contributions on foundations of Chance
Discovery, computational mechanisms, human processes, and fielded
applications. Indicative topics are given below.
Foundations of Chance Discovery
-- Frameworks for interactive Chance Discovery
-- The role of abduction and induction
-- Logic-based frameworks for Chance Discovery
-- Theories from the perspective of Complex Systems
Processes of Human Chance Discovery
-- Social cognition to guide the collaborative assessment of chances
-- Communicative processes that form the basis of scenario creation
-- Cognitive processes of becoming aware of a chance and explaining
its significance.
Computational Mechanisms of Chance Discovery
-- Identifying rare or novel events
-- Becoming aware of significant events
-- Interaction with comprehensive, communicable and understandable
visualisations
- -- Computational understandable chances vs. human understandable chances
- -- Explaining and evaluating events where decision-makers still have
to become aware of its significance (hidden event).
Applications of Chance Discovery
-- Identification of new trends
-- Scenario management
-- Collaborative approaches
-- Specific application domains such as
-- risk management,
-- diagnosis
-- economical forecasting
-- supply management,
-- sales strategies
-- marketing strategies
-- intelligent Web design and Web search,
-- computer-based training,
-- team-work support.
-- creativity support
-- product design,
-- side-effects of new drugs,
All these applications have in common that decision-makers became
aware of the significance of a rare event and did not ignore it as
noise. They rather used it to create new trends that were more
effective than predictions, which were based exclusively on past
observational patterns.
Paper format, paper limit, and submission address
The paper format should follow the LNCS style guidelines of Springer Publi
shers:
http://www.springeronline.com/sgw/cda/frontpage/0,10735,5-164-2-72376-0,00
.html
The paper should not exceed 10 pages and should be sent by email as
TEX/WORD file and as PDF file before the submission deadline to the
following address:
Ruediger Oehlmann, UK
Kingston University London
School of Computing and Information Systems
Cognitive Science Laboratory
Penrhyn Road
Kingston upon Thames. KT1 2EE, UK
email: [EMAIL PROTECTED]
Important dates:
2005 April 1 Submission deadline
2005 April 22 Notifying authors about acceptance
2005 May 13 Submitting the final paper by email to the Discovery
Workshop Chair
Review and Publication:
All submissions will be reviewed on the basis of relevance,
originality, significance, soundness and clarity. All accepted papers
will be published in workshop working notes. Working notes of the
workshop will be made available to participants in electronic form
prior to the conference. They will also be distributed at the
conference itself (CD and paper version). In addition, if we receive a
sufficient number of high quality contributions, we intend to publish
selected papers as a book.
Co-Chairs:
Ruediger Oehlmann, UK
Kingston University London
School of Computing and Information Systems
Cognitive Science Laboratory
Penrhyn Road
Kingston upon Thames. KT1 2EE, UK
email: [EMAIL PROTECTED]
Yukio Ohsawa, Japan
The University of Tsukuba
Graduate School of Business Sciences
3-29-1 Otsuka, Bunkyo-ku,
Tokyo 112-0012, JAPAN
[EMAIL PROTECTED]
Akinori Abe, Japan
ATR Intelligent Robotics & Communication Labs.
2-2-2, Hikaridai, Seika-cho, Soraku-gun,
Kyoto 619-0288 JAPAN
[EMAIL PROTECTED]
Program Committee:
Akinori Abe, Japan
Eugenio Alberdi, UK
Klaus-Dieter Althoff, Germany
David Bergner, USA
Sung-Bae Cho, Korea
Renate Fruchter, USA
David E. Goldberg, USA
Andreas Hotho, Germany
Ralf Klinkenberg, Germany
Xavier Llora, USA
Lorenzo Magnani, Italy
Peter McBurney, UK
Yumiko Nara, Japan
Ruediger Oehlmann, UK
Yukio Ohsawa, Japan
Enric Plaza, Spain
Paolo Remagnino, UK
Hiroko Shoji, Japan
Katsuaki Tanaka, Japan
Katsutoshi Yada, Japan
Ikuko Yairi, Japan
Qinfu Zhang, UK
Edward Tsang, UK
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