PKDD-2001 Call for Papers 

The two conferences will be closely co-ordinated. There will be a single electronic submission procedure: authors can indicate whether they submit their paper to ECML'01, PKDD'01, or both. In the latter case, the topic of the joint submission must be within the scope of both conferences. A joint submission will be reviewed by three PC members, one of whom is a member of both Program Committees. In case of acceptance to both conferences, the authors decide in which proceedings to publish their paper. Selected joint submissions will be presented during the overlap day.

The proceedings of both conferences will be published as separate volumes by Springer-Verlag in the Lecture Notes in Artificial Intelligence series and will be available during the conference.

Timetable

Electronic titlepage due:	Friday, 6 April, 2001, noon Central European Time
Submission deadline:	Wednesday, 11 April, 2001, noon Central European Time
Notification:	Friday, 25 May, 2001
Camera-ready copy:	Monday, 18 June, 2001

Further details regarding electronic submission, submission requirements and types of submissions will be posted at the conferences' website at

http://www.informatik.uni-freiburg.de/~ml/ecmlpkdd/instructions_for_authors.html

Call for Papers

Data Mining and Knowledge Discovery in Databases (KDD) have emerged from a combination of many research areas: databases, statistics, machine learning, automated scientific discovery, inductive logic programming, artificial intelligence, visualization, decision science, and high performance computing. While each of these areas can contribute in specific ways, KDD focuses on the value that is added by creative combination of the contributing areas. The goal of PKDD'01 is to provide a European-based forum for interaction among all theoreticians and practitioners interested in data mining. Interdisciplinary collaboration is one desired outcome, but the main long-term focus is on theoretical principles for the emerging discipline of KDD and on practical applications of discovery systems that are built on those principles. We seek the KDD-specific principles that go beyond each contributing area. We seek a new generation of applications that go beyond applications developed in each contributing area.

The proceedings of PKDD'01 will be published by Springer-Verlag in the Lecture Notes in Artificial Intelligence series and will be available during the conference.

Topics of interest (not limited to)

• The KDD process: business problems and their data mining solutions, data cleaning, dimension reduction, discretization, data and results visualization, quality assessment, the use of prior knowledge.
• Methods and Algorithms: relational mining, multi-relational mining, mining beyond relations (text, web, multimedia, time-series, ...), scalable algorithms, incremental algorithms, anytime algorithms, methods of statistics and scientific discovery.
• Foundations of Data Mining and relations with statistics, artificial intelligence, databases and other fields.
• Systems: integration with databases, integration with OLAP, with data warehouses and statistics software, parallel and distributed mining, interactive mining, embedded mining, scalability.
• Applications: bioinformatics, medicine, marketing, finance, engineering.

See the conferences' website for the list of PKDD'01 Program Committee members and further details regarding the submission procedure:

http://www.informatik.uni-freiburg.de/~ml/ecmlpkdd/instructions_for_authors.html

PKDD'01 Program Chairs

Luc De Raedt Dept. of Computer Science Albert-Ludwigs University Freiburg Georges Köhler-Allee, Geb. 079 D-79110 Freiburg i.Br. Germany	Arno Siebes Inst. for Information and Computing Sciences Utrecht University Padualaan 14 3584 CH Utrecht The Netherlands
www.informatik.uni-freiburg.de/~deraedt/ E-mail: deraedt@informatik.uni-freiburg.de Phone: +49 (761) 203-80 05 Fax: +49 (761) 203-80 07	www.cs.uu.nl/staff/siebes.html E-mail: siebes@cs.uu.nl Phone: +31 (30) 253 3229 Fax: +31 (30) 251 3791