13th European Conference on Machine Learning (ECML'02)
6th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'02)
19-23 August 2002
http://ecmlpkdd.cs.helsinki.fi/
The 13th European Conference on Machine Learning (ECML) and the 6th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD) will be co-located in Helsinki, Finland, in August 2002. Co-ordination of the two conferences provides ample opportunities for cross-fertilization between the two areas, and follows the success of jointly organized ECML/PKDD in 2001.
KDNet will select the best papers of both PKDD and ECML, and will honour both with an award of 1000 euros each. The awards will be based on significance and originality of contributions. The selection is made by KDNet and is based on suggestions by the Program Committee.
The European Conference on Machine Learning series is intended to provide an international forum for the discussion of the latest high quality research results in machine learning and is the major European scientific event in the field. Submissions are invited that describe empirical and theoretical research in all areas of machine learning. Submissions of papers that describe the application of machine learning methods to real-world problems are encouraged.
Topics of interest (non-exhaustive list):
abduction
analogy
artificial neural networks
bayesian networks
case-based reasoning
cognitive modelling
computational learning theory
cooperative learning
evolutionary computation
genetic learning
grammatical inference
inductive learning
inductive logic programming
information retrieval and learning
knowledge acquisition and learning
knowledge base refinement
knowledge intensive learning
machine learning of natural language
multi-agent learning
multistrategy learning
pattern recognition
planning and learning
reinforcement learning
revision and restructuring
robot learning
statistical approaches
vision and learning
Data Mining and Knowledge Discovery in Databases (KDD) is 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 is to provide a forum for interaction among all theoreticians and practitioners interested in data mining.
Topics of interest (non-exhaustive list):
anytime algorithms
applications
database integration
dimensionality reduction
discretization
distributed mining
incremental algorithms
inductive databases
interactive mining
knowledge discovery process
multimedia mining
OLAP and data warehouse integration
personalization and adaptivity
parallel mining
relational mining
scalable algorithms
scientific discovery
text mining
time-series mining
visualization
web mining
There is a single electronic submission procedure: authors indicate whether they submit their paper to ECML, PKDD, or both. In the latter case, the topic of the joint submission must be within the scope of both conferences; accepted joint submissions are assigned to the more appropriate of the conferences. All submissions will be reviewed by the respective program committees.
The paper should be formatted according to the Springer-Verlag Lecture Notes in Artificial Intelligence guidelines. Authors' instructions and style files can be downloaded from http://www.springer.de/comp/lncs/authors.html. The maximum length of papers is 12 pages.
The proceedings of both conferences will be published by Springer-Verlag in the Lecture Notes in Artificial Intelligence series and will be available in the conference.
Submission deadline: Wednesday 27 March 2002
Notification of acceptance: Monday 6 May 2002
Camera-ready copies due: extended to Friday 31 May 2002
For details of the submission procedure, see the conference website at http://ecmlpkdd.cs.helsinki.fi/
Tapio Elomaa, University of Helsinki
Heikki Mannila, Helsinki Institute for Information Technology and Nokia Research Center
Hannu T. T. Toivonen, University of Helsinki and Nokia Research Center
For more details, see the conference website at http://ecmlpkdd.cs.helsinki.fi/