Dear UAI Community,
In KES'2000 (Fourth International Conference on Knowledge-Based Intelligent
Engineering Systems & Allied Technologies 30, 31 August, 1 September 2000,
see http://luna.bton.ac.uk/~kes2000/ for details) I am organizing a special
session on "chance discovery" from data. Although this is a small organized
session, I welcome submissions by people newly interested in chance
discovery.
Chance discovery means to find signs which have possibility to become
benefits or risks in future management of a company or future life of people,
from existing data. The difference from "prediction" is that a chance may
not really affect the future if people ignore the chances or avoid the risks.
"The best way to predict the future is to invent the future" and chances
serve as hints for inventing or surviving the future. In other words, a
chance is an entrance into the way of inventing or surviving the future,
rather than the future itself - one has to open the door and walk through it.
Let me show a small example:
When the first paper about genome analysis appeared in the AI area as a
new application of AI tools, the AI community could not predict it would
make a significant trend: There was no time-series of the frequency of
"genome analysis" on which to predict the increase of the word's frequency,
because this was the first paper. Thanks to the efforts of advertising
genomes as a chance to appeal the usefulness of AI tools, however, we now
have a plenty of AI researchers contributing to genome analysis.
Such a promotion is a human-information interaction for making the chance,
i.e., "genome analysis" in fasion. Imagine that the paper was
a book ... the book seller could have caught a sales chance by advertising
the book to both communities of bilology and AI, or by promoting a forum
gathering people from AI community and biology community.
If you take "chance" as risk, it is also meaningful to find risks and the
reasons for the existence of risks. By knowing the reasons, one can plan
the actions for avoiding the risks, or avoid panics. The contribution of
chance discovery to marketing, product development, and many other
situations in human life is expected to be significant, according to
professionals in domains directly relevant to human life.
The paper dead line is May 15th, by which no more than 4 pages of IEEE
format in
http://luna.bton.ac.uk/~kes2000/#papers
http://luna.bton.ac.uk/~kes2000/guide.htm
is welcomed to be sent to me ***electronically***. The most welcomed style
is a postscript file, gzipped and uuendoded. Please kindly e-mail me
your will to submit and a short paper abstract, before you submit the paper
(if you have some reason for submission delay, please include it in the
e-mail).
Also, I and other forty people interested in chance discovery from data are
going to organize a mailing list soon. People interested in this ML are all
welcomed to join us by mailing <matumura@miv.t.u-tokyo.ac.jp>. At the first
stage we will make a simple (alias) version and then develop it further.
Thank you for your kind attentions.
Sincerely,
Yukio OHSAWA
Dr. Eng, Associate Professor in University of Tsukuba
3-29-1 Otsuka, Bunkyo-ku, Tokyo 112-0012 Japan
Fax: +81-3-3942-6829
e-mail: osawa@gssm.otsuka.tsukuba.ac.jp
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