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):

• Analysis of human behaviour.
• Analysis of complex systems (society, community etc.).
• Applications of Chance Discovery.
• Characterization of ``Chance.''
• Logical foundations for Chance Discovery.
• Theories and methodologies to discover rare or novel events.
• Theories and methodologies to foretell next trends.
• Theories and methodologies to make aware of significant events.
• Theories and methodologies for an evaluation and selection of chance.
• Models and methodologies for effective suggestion of chance.
• Relationship between computational and manual methods.
• Integration of computational and manual methods.

Submission:

The papers can be submitted to (both):

• KES submission system (PROSE)
  http://kes2007is.prosemanager.com/submitpaper.asp
  Please select IS02 - Chance Discovery

  Akinori Abe (ATR)

  ave@ultimaVI.arc.net.my

Important Dates:

• 1 March, 2007: Submission deadline of papers
• 15 April, 2007: Notification of acceptance of papers. (extended)
  sorry... review process is delayed.. We will send you notification ASAP.
• 25 April, 2007: Deadline for revised papers (extended....)
• 1 May, 2007: Deadline for camera-ready papers (via PROSE)
  attention!!
  The final publication files (editable word processor source not PDF) must be uploaded onto PROSE by 1 May 2007.
• by 1 June 2007: All presenting authors in the Invited Session must register with payment for their papers to appear in the proceedings.
• 12,13 or 14 September, 2007: Session

Review:

Publication:

Chairs:

Akinori Abe