Chance Discovery(人の意思決定の決め手になる新希事象の発見)はもともと
データマイニングの一環として提起した問題なのですが、構築中のシステム出
力結果などをしょって最近幅広くコメントを求める旅を重ねる中で、計算機に
よる解析もさることながら、発見した事象を元に意思決定を行う人間の考察の
重要さを認識するようになりました。

  それで、できることなら幅広い視野での議論を深め、健全に進展できればと
思い、オーガナイザの責任でということでプログラム委員長の許可を得まして
公募〆切を延ばしました次第です(もとは5/15でした)。どうぞふるってご参加
下さい。参加枠は事情によっては増やせると思います。私は認知科学の研究者
と広い親交がないのですが、その方面の方々にもご転送頂けますと幸いです。


******************************** IEEE ************************************
************* KES 2000, Special Session on Chance Discovery *************
  (Knowledge-Based Intelligent Engineering Systems & Allied Technologies)
************* 30, 31 August, 1 September 2000, Brighton UK **************
                   http://luna.bton.ac.uk/‾kes2000/ 
*************************************************************************

*** SCOPE *** 
- The best way to predict the future is to invent the future (Alan Kay) -- 

A chance means a new event, which has possibility to become a significant
advantage (damage) in the future life of people, if appropriate efforts 
are (are not) made. The difference of discovering chances from predicting
the future is that chances may not really affect the future if people 
ignore the chances or avoid the risks.  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.

Two essential points of a chance (or a risk) are:
- A chance is not a sheer repetition of past success, but a trigger
  of a new and significant progress. A source of chance is the explosion
  of potential motivations, e.g. potential desires of customers in a market.
- New chances are more beneficial than past frequent success-patterns, 
  because new chances are not known yet by your rivals. 
- New risks are more dangerous than past frequent damage-patterns, 
  because you do not know how to avoid them. 

Example 1: When the first rain-umbrella appeared in London, people could 
not tell it would become a popular fashion - they rather felt it strange 
to walk the street with an umbrella.  The difficulty of prediction is
here: there was no time-series of umbrella sales before the first umbrella.
   But this was a chance anyway -- thanks to the efforts of advertising 
the merit of umbrella "umbrella protects you from rain," it prevailed around 
the world. This promotion is a human-information interaction for putting 
the chance (umbrella) into a real future fashion. If the umbrella seller 
was aware that walking with an umbrella looked strange, he could have found 
a chance of selling coats matching with an umbrella. 
   Here we find it essential to stimulate potential motivations (i.e. the 
desire to avoid rain in London, and the sense of fashion of people in London),
for putting a chance into a success.  How can we discover the link between
the potential (unknown) motivations and the new product which is unknown, 
without frequent patterns in the past ?

Example 2: When small earthquakes occurred in Kobe and the north of Osaka
(in Japan) from 1980's, people could not tell what they meant. In fact this
was a fatal risk -- due to the stress in the land crust of Kobe, between the 
north of Osaka and the trough in the south-east of Japan, 6600 people were
victimized from the big one of M7.2 in Kobe, 1995.  If we knew that the past
small earthquakes were causing heavy stress at the focal active fault of 
1995, the risk would have been recognized and many people could have been 
helped.
   Here we find it essential to know the potential causes od risk, for 
avoiding a disaster.  How can we discover the link between the potential 
(unknown) causes and the new disaster which is unknown (an earthquake of 
M7.2 is a totally different event from one of M3.0 in the past, even if 
both occurred in the same fault which quaked in the past), without frequent 
past patterns ?

For both examples, the key issue is focusing attention to a new event which 
is significant for the future, not discarding it as a noise only because it
is unknown.  For telling the significance here, human-information interaction 
for telling the link between the potential motivations and the new event is 
highly contributing to chance discovery. 

Many on-going researches including the discovery of 
- new products worthy to promote the sales, and
  new good customers to send advertising mails, for exploding the sales
- new risks which should be avoided in business and human life, e.g.
  new side-effect risks of a drug to appear in novel situations
- new keywords in research papers showing pionieering and meaningful 
  directions of research
- new keywords in WWW which show attracting future trends
and information visualizations, for telling how to put the chance into a real
merit and how to avoid the risk, are very relevant to the session.  New 
assertions about chance discovery on previous data are welcomed, as well as 
new data presenting chances.


*** PAPER SUBMISSIONS *** 
The tight (and strict) paper dead line is June 10th, 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, as soon as possible.