KES2007 invited session on Chance Discovery

12, 13 & 14 September 2007
Vietri sul Mare, Italy

Paper lists to be presented
Session Themes: [Chance Discovery: Genaration, evaluation, and suggestion of a Chance.]
Session Subtitle: Chance: logical formalisation VS human factors.

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 in the future. 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 simply predicting the future.

This session will discuss several problems in Chance Discovery. As shown, Chance Discovery is a research to study how to discover rare or novel events causing potentially significant situation. Although the event itself could not be significant. A chance might be computationally or manually discovered. Thus, advanced computational techniques such as abduction and induction (including data mining) could be applied to Chance Discovery. In addition, personalised and very traditional (sometimes, manual) data mining method could also be effective in Chance Discovery. We have discussed limitations of conventional data mining methods. And many new computational methods, and concepts and mechanisms of human discovery have been proposed. In the contexts, we have discussed how to discover and suggest events causing significant but hidden events. Our common understandings are that we deal with events in the real world, therefore, we need to have knowledge about movement in society, behaviour of people, as well as computational methods. In addition, it is important to discuss effective chance evaluation, selection, and suggestion methods.
Thus, we would like to discuss from computational, cognitive, sociological, economical and psychological viewpoints. In addition, we would like to discuss relationship and integration of computational and human aspects of Chance Discovery. Of course, other viewpoints are also welcome!

Topics to be discussed (will not be restricted to):


Page formatting: For formatting information, please see Springer Information for LNCS Authors (See ``Proceedings and Other Multiauthor Volumes - Using Microsoft Word" etc.).
Please note that papers should be no longer than eight pages in LNCS format. Papers longer than this will be subject to an additional page charge. All oral and poster papers must be presented by one of the authors who must register and pay fees.
Submissions are invited on previously unpublished research.

The papers can be submitted to (both):

Important Dates:


All submissions will be reviewed on the basis of relevance, originality, significance, soundness and clarity. At least two referees will review each submission independently.


All accepted papers will be published in the KES2007 Proceedings (LNCS/LNAI, Springer-Verlag).


Akinori Abe

ATR Knowledge Science Laboratories
2-2-2, Hikaridai, Seika-cho, Soraku-gun, Kyoto 619-0288 JAPAN
Yukio Ohsawa
The Univeristy of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656 JAPAN

Previous invited sessions in KES: