New direction for chance discovery?

The issue on chance discovery (volume 11, issue 5) is guest edited by Akinori Abe and Yukio Ohsawa. Since 2000, invited sessions on chance discovery have been organized in KES conferences (www.kesinternational.org). In this issue, nine papers which are extended version of sessions' paper and newly submitted are selected.

A full list of contents can be read further on, but as a whole, the keywords for this issue are ‘interaction’, ‘visualization’ and ‘abduction’ that are contributive to the basic methodologies of chance discovery. And, for application, the management and discovery of risks, in which stock price movements are to be included, are appeared as core issues.

The real lives of humans are complex and the future is not predictable. In order to have better –or the best- benefits, it is necessary to predict the future trends. In the usual case, data mining techniques provide us with satisfactory enough results for doing good business. However, there are exceptional events where simple data mining techniques and statistical analysis don’t suffice.

If the risk can’t be predicted, the result may be serious. There are implicit (not noticed due to the rarity or the novelty) events which can be signs for fatal, or sometimes for an extremely beneficial, scenario. Because these signs are novel, and hard to be related to the result, it has been difficult to catch them for making a suitable decision at a suitable time. It is important to determine implicit symptoms to risks or benefits (opportunities). Accordingly, Ohsawa proposed chance discovery in 2000.