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******** ******** Call for Papers ******** ********
Special Session: Chance Discovery on Human-Data Interaction
Sixth International Conference on Knowledge-Based Intelligent Information Engineering Systems
(KES 2002)
16, 17, and 18 September 2002
Podere d'Ombriano, Crema, Italy
Web site address:
http://www.miv.t.u-tokyo.ac.jp/~matsuo/KES2002/
http://www.bton.ac.uk/kes/kes2002/
<The Scope of Chance Discovery>
Chance Discovery is a recently developing field aims to support human
decision making through human-data interaction. We welcome various fields
of research which is at least potentially related to human decision making.
Chance discovery is the discovery OF chance, rather than discovery BY chance.
A "chance" here means a new event/situation that can be conceived either as
an opportunity or as a risk. The "discovery" of chances is of crucial importance
since it may have a significant impact on human decision making. Desirable effects
of opportunities should be actively promoted, whereas preventive measures should
be taken in the case of discovered risks. In other words, chance discovery aims
to provide means for inventing or surviving the future, rather than predicting the future.
The essential aspect of a chance (risk or opportunity) is that it can be the seed
of new and significant changes in the near future. The discovery of new opportunities
might be more beneficial than reliance on past frequent success-patterns,
because they are not known yet by one's business rivals. The discovery of new risks
might be indispensable to avoid or lessen damage, because they cannot be explained
by past frequent damage-patterns. Therefore, being aware of a novel important event
without ignoring it as noise in the data is essential for human future success.
Besides data mining methods for finding rare but important events from time-series,
it is also important to draw humans attention to such events, i.e., to make humans
ready to catch chances. In this sense, human-information interactions are highly
relevant to chance discovery. Furthermore, chance discovery can be seen as
an extension of risk management to computer-aided problem solving where novel
situations are involved.
This workshop is intended to bring together researchers from artificial intelligence,
human-computer interaction, social and cognitive sciences, risk management,
knowledge discovery and data mining, and other related domains, for stimulating
discussions on chance discovery.
<Instructions for Authors>
* Papers must be written in English (4 pages maximum).
* Include the contact author's full name, address, telephone-, fax-
numbers, and E-mail address.
* Include presenter address and his/her 4 line resume for introduction
purposes only.
* The conference proceedings will be published by IOS Press.
Papers must conform to the requirements specified in the IOS Instructions
for the Preparation of a Camera-Ready Manuscript.
(http://www.bton.ac.uk/kes/kes2002/instruct.doc)
* Please submit the paper by an e-mail, as a PS, PDF, of a Microsoft Word
DOC file, to the organizer directly.
Do not address to the program committee of KES 2002.
If you prefer other type of manuscript, please notify us in the submission,
and be sure you have some risk of being rejected for that reason.
* All papers will be refereed by at least two experts in relevant fields.
<Organizers of the session>
Hiroko SHOJI
- -- Associate Professor, Dept. of Informatics Education
Faculty of Education, Kawamura Gakuen Women's University
Address: Kawamura Gakuen Women's University 1133 Sagedo,
Abiko-shi, Chiba 270-1138 Japan
Fax: +81-471-83-0115
E-mail: hiroko@da2.so-net.ne.jp
Yutaka Matsuo
- -- Graduate School of Engineering, University of Tokyo
Address: University of Tokyo, Hongo 7-3-1, Bunkyo-ku, Tokyo
113-8656, Japan
Fax: +81-3-5802-8213
E-mail: matsuo@miv.t.u-tokyo.ac.jp
<Important Dates>
Receipt of papers: 1 April, 2002
(If your situation hinders you from meeting the deadline, please consult the organizer.)
Notification of acceptance: 1 May, 2002
--- Yutaka MATSUO and Hiroko SHOJI: Organizers of the session
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