ECML PKDD 2008

Submit papers as PDF or DOC files (up to 12 pages) to
http://www.easychair.org/conferences/?conf=sokd08

Papers must be in English, formatted according to the Springer-Verlag Lecture Notes in Artificial Intelligence guidelines. Authors instructions and style files can be downloaded at
http://www.springer.de/comp/lncs/authors.html.

A major challenge for third generation data mining and knowledge discovery systems is the integration of different data/knowledge resources (which are highly diverse in nature in terms of representation and data formats) and computer systems (tools for data integration, data mining and knowledge discovery) which are distributed across the network.

Paper deadline: June 16 Extended to June 20th
Notifications of Acceptance: July 16 Delayed until July 25th
Final versions: August 10 (18:00 GMT+1)

8.00 - 9.15: opening of the workshop

9.15 - 9.35: J. de Bruin, J. Kok, N. Lavrač, and I. Trajkovski: Towards Service-Oriented Knowledge Discovery: A Case Study

9.35 - 9.55: J. Wicker, C. Brosdau, L. Richter, and S. Kramer: SINDBAD SAILS: A Service Architecture for Inductive Learning Schemes

9.55 - 10.15: J. Vanschoren, H. Blockeel, B. Pfahringer, and G. Holmes: Organizing the World’s Machine Learning Information

10.15 - 10.40: coffee break

Workshop chairs

Nada Lavrač
Joost Kok
Jeroen de Bruin
Vid Podpečan

Program Committee

Farhad Arbab
Michael Berthold
Hendrik Blockeel
Werner Dubitzky
Axel Hahn
Arno Knobbe
Filip Zelezny

Nada Lavrač (nada <dot> lavrac <at> ijs <dot> si)
Joost Kok (joost <at> liacs.nl)
Jeroen de Bruin (jdebruin <at> liacs.nl)
Vid Podpečan (vid <dot> podpecan <at> ijs <dot> si)

This workshop intends to gather contributions supporting third generation data mining and knowledge discovery, elaborating a service-oriented approach to information fusion, for the needs of exploratory data analysis in the framework of inductive databases, enriched with ontology information available from the web.

Given the growing amount of information available on the net, this workshop will be of interest to knowledge engineers, as well as students and researchers interested in data mining and advanced methods for knowledge discovery.