KES2014 invited session on Chance Discovery and Market of Data

15, 16 & 17 September 2014

Gdynia, Poland

A submission link is ready!!! (31 Jan, 2014)

*** Paper due has been extended to 30 April!! ***



Session Themes: [Chance Discovery: Chance Discovery and Market of Data]

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. It would be a gate for fantastic and innovative applications.
Thus, we would like to discuss from logical, computational, cognitive, sociological, economical and psychological viewpoints. In addition, we would like to discuss ``curation'' of chance. Traditionally, curation is not only concerned with long-term care of books, paintings or other artefacts. It is also about maintaining their integrity and enabling and promoting their availability to appropriate audiences (http://www.jisc.ac.uk/e-sciencecurationreport.pdf). In addition, ``curation'' has recently focused on even in the marketing field. As shown above, for chance discovery, we have focused on strategies to discover rare or novel events and those to present hints of chance to users. By curation, we add a more active action to chance discovery, which curators usually struggle to explicitly or implicitly express extended or hidden meanings (values) to potential audiences. It should be related to ``value sensing'' in chance discovery. And, it should be related to ``chance sysnthesis.''
In addition, we would like to discuss how to create and design the market where data are reasonably dealt with, i.e., sold, opened free, or shared after negotiation. Our ultimate goal is to have each people on the earth feel free to share one's own data with others without fearing of the loss of business opportunities.
In order to make a social environment where analysts and decision makers in active businesses and sciences can be provided with data they need, in this workshop we also aim to (re)design an environment called the Market of Data, where each user or provider of data can understand the value of each part of data so that one can buy/sell it for a reasonable price. Here, the value of each part of data shall be visualized to aid users' considering its possible contribution to promoting/creating businesses and scientific findings.
Of course, other viewpoints are also welcome!

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

Submission:

Page formatting: The preferable length for full papers is 6 to 8 pages (10pp. maximum).
Guidance notes for the preparation of Full Papers is available here.
An MS Word template is available here.
For LaTex user, a package ecrc-procs.rar can be used.
For a paper to be published in the Procedia proceedings It is the author's responsibility to ensure that their paper does not contain any errors. Also, kindly note that Elsevier will publish what they receive so it is important that the authors submit the final version of their papers.
Proofs will not be sent to authors at any time during production.
Submissions are invited on previously unpublished research.

Your papers can be submitted to (both):

Important Dates:

Review:

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

Publication:

All accepted papers will be published in the KES2014 Proceedings (Procedia Computer Science).
Extended versions of selected papers will be considered for publication in the KES Journal (International Journal of Knowledge-Based and Intelligent Engineering Systems) published by IOS Press, and other journals.

Chairs:

Akinori Abe
Faculty of Letters, Chiba University
1-33 Yayoicho, Inageku, Chiba 263-8522, JAPAN
E-mail: ave@ultimaVI.arc.net.my
Yukio Ohsawa
The Univeristy of Tokyo
7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8656 JAPAN
E-mail: y.ohsawa@gmail.com
Noriyuki Kushiro
Kyushu Institute of Technology
680-4 Kawazu, Iizuka-shi, Fukuoka, 820-8502, JAPAN

Previous invited sessions in KES: