Subject: 2nd CfP KI-Workshop: LEARNING FROM LARGE DATASETS; KNOWLEDGE DISCOVERY IN DATABASES
From: Rob Engels <[email-masked]>
To: [email-masked], [email-masked], [email-masked], [email-masked], [email-masked]
Cc: Robert Engels <[email-masked]>, Guido Lindner <[email-masked]>
Date: Tue, 29 Apr 1997 16:55:02 +0200 (MET DST)

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                     2nd Call for Papers

                         KI-97 WORKSHOP
               "LEARNING FROM LARGE DATASETS; 
               KNOWLEDGE DISCOVERY IN DATABASES"

                      In conjunction with the:
         21st Annual AI-meeting '97 (KI-Jahrestagung '97)
                  Freiburg  9.9 - 12.9  1997
                  Baden-Württemberg, Germany

   www-adres:  http://www.aifb.uni-karlsruhe.de/WBS/KI97/KI97.html

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Description 
As more and more Machine Learning applications become available, 
the question how to embed such techniques in real world applications is 
of increasing interest. In the past years an increasing number of workshops 
in this area were held, and more and more fielded application are known. 
For the Knowledge Discovery in Databases (KDD) community there is an additional
aspect that plays an important role. Many interesting domains for learning are represented in large databases.

For AI research, the topic of learning is interesting not at least
because of the possibilities w.r.t. automated knowledge acquisition,
generation and refinement of models of expert knowledge, verification of
hypothesises and concept learning. Also, when performing KDD, topics from
many fields that are regarded as 'typical' for AI play an important role.
One might think of knowledge representation for defining language biases on
the learning data and the generated knowledge, knowledge about
classification, diagnosis together with planning and Case Based
Reasoning-like techniques for defining KDD processes.

The focus of the current workshop will be on, but is not limited to the 
following topics:

- (Methodological) Approaches for support of complete KDD-processes 
  and especially support for the generation of KDD-processes and the
  identification of the types and the roles of knowledge in KDD-processes.

- Fielded applications that describe approaches within their contexts.
  Interesting papers should deal with the assumptions and constraints that
  play a role in the definition of those applications.

- Techniques for data analysis in large databases.

- Techniques that deal with data pre- and postprocessing, and their
  implications for the results of data analysis.

- Description and comparison of learning techniques 'at the Knowledge
  Level'. Aimed is at abstraction from implementational issues.

- Representation and decomposition of KDD tasks, ranging from natural
  language interpretation to task descriptions using formal representation
  mechanisms that allow for goal definitions.

This workshop does not focus on (methods for) developing new algorithms. 
Moreover, preference is given to case studies trying to show the general application principles that can be derived from them. 

Submission guidelines: 
* Submitted papers should not exceed 8 pages using the Times Roman 12pt font.
* The title page should contain paper title, author names, affiliations and 
  full addresses including e-mail of the corresponding author, as well as the
  paper abstract and at maximum five keywords 
* Papers are reviewed by at least two members of the program committee
  on their relevance for the workshop discussions. 

Workshop program

The focus of the workshop will be on a good, informal atmosphere to encourage discussions. The workshop is planned for one day, with a maximum
of 10 paper presentations. If quality and quantity of submitted papers
allow us, we plan to have a poster session during the coffee break. 
Presentations will be 30 minutes long (including a 10 minute discussion). 
We like to put emphasis on discussions, so this 30 minute presentations 
are not fix, i.e. when interesting discussions arise, we will be flexible.

In order to stimulate discussion during the workshop, accepted papers will
be available via WWW beforehand (see WWW-pages).

Intended Participants and Audience
 
The workshop primarily aims at scientists and practitioners that apply
ML and related techniques to solve practical problems. To attend the 
workshop, one should submit a paper, a one page extended abstract or a 
statement of interest. In case of too many submissions, the program 
committee selects participants on the contribution a participant to the 
workshops discussion. 
Ideally, the audience contains a mix of university and industrial participants. 

Tentative Submission Schedule
* Submission deadline:             April 15st, 1997
* Notification of acceptance:        May 15th, 1997
* Camera ready copy + PS-file:      July 15th, 1997
* Papers available on WWW:         August 1st, 1997
* Workshop date:                September 9th, 1997

Submissions as a 3-fold hardcopy as well as a PostScript file to:

Robert Engels                              Tel.:+49-(0)721-608 3924 
Universitaet Karlsruhe                     Fax.: +49-(0)721-693 717 
Institut AIFB                  E-mail: [email-masked] 
D-76128 Karlsruhe                                                      
Germany                                                             

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Organising Committee

Robert Engels,    University of Karlsruhe, Germany
Guido Lindner,    Daimler Benz AG Research and Technology, Germany

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Program Committee:
A. Arning (IBM) 
R. Kruse (University of Magdeburg) 
Ch. Lingenfelder (IBM Germany) 
P. Lockemann (Inst. IPD, University of Karlsruhe, Germany) 
G. Nakhaeizadeh (Daimler Benz AG Research, Ulm, Germany) 
H. Richter (University of Kaiserslautern) 
R. Studer (Inst. AIFB, University of Karlsruhe, Germany) 
S. Wrobel (GMD) 
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