(Apologies if you receive multiple copies of this CFP)

Call For Papers
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Special Issue of IEEE Transactions on Evolutionary Computation on
Data Mining and Knowledge Discovery with Evolutionary Algorithms

Data mining (DM) consists of extracting interesting knowledge from
real-world, large & complex data sets; and is the core step of a broader

process, called the knowledge discovery from databases (KDD) process.
In addition to the DM step, which actually extracts knowledge from
data, the KDD process includes several preprocessing (or data
preparation)
and post-processing (or knowledge refinement) steps. The goal of data
preprocessing methods is to transform the data to facilitate the
application of a (or several) given DM algorithm(s), whereas
the goal of knowledge refinement methods is to validate and
refine discovered knowledge.
Ideally, discovered knowledge should be not only accurate,
but also comprehensible and interesting for the user.
The total process is highly computation intensive.

The idea of automatically discovering knowledge from databases
is a very attractive and challenging task, both for academia and for
industry. Hence, there has been a growing interest in data mining in
several AI-related areas, including evolutionary algorithms (EAs).
The main motivation for applying EAs to KDD tasks is that they
are robust and adaptive search methods, which perform a
global search in the space of candidate solutions (for instance,
rules or another form of knowledge representation). Intuitively, the
global search performed by EAs can more effectively discover
interesting patterns that would have been missed by the greedy
search performed by many KDD methods.

The EA community has been publishing KDD-related articles
in a relatively scattered manner in journals dedicated to knowledge
discovery and data mining or evolutionary computing.
The objective of this issue is to assemble a set of high-quality
original contributions that reflect and advance the state-of-the-art
in the area of Data Mining and Knowledge Discovery with
Evolutionary Algorithms.
The special issue will emphasize the utility of different evolutionary
computing tools to various facets of KDD, ranging from theoretical
analysis to real-life applications.

Manuscripts should be prepared as per the format of the journal
available at its web site:
http://www.ewh.ieee.org/tc/nnc/pubs/tec/.
Submission should be made to the guest editors
(electronic submissions in postscript or PDFare preferred)
at ash@... or alex@....

All submissions will be peer reviewed as per the norm of the
IEEE Tr. on Evolutionary Computation.

If the submission is sent by regular mail, authors are requested
to send six copies of their manuscripts to one of the following address:

Dr. Ashish Ghosh
Machine Intelligence Unit
Indian Statistical Institute
203 B. T. Road
Kolkata 700 108
INDIA
http://www.isical.ac.in/~ash

or

Dr. Alex A. Freitas
PUCPR (Pontificia Universidade Catolica do Parana)
PPGIA - CCET
Rua Imaculada Conceicao, 1155
Curitiba - PR, 80215-901
BRASIL
http://www.ppgia.pucpr.br/~alex

Topics of interest include (but are not restricted to):

Evolutionary algorithms (EAs) for data preprocessing
(e.g., data cleaning, attribute selection, attribute
construction),
data mining (e.g., classification/prediction, clustering,
dependence
modeling, regression, extraction of comprehensible &
interesting
knowledge), or post-processing of extracted knowledge
Comparison between EA based and other methods for KDD tasks
Tailoring operators of EAs for KDD tasks
Incorporating domain knowledge in EAs
KDD with evolutionary intelligent agents
Hybrid (e.g., neuro-evolutionary, rule induction-evolutionary,
fuzzy-evolutionary) EAs for KDD
Mining semi-structured or unstructured data (e.g., web mining,
text mining) with EAs
Integrating EAs with database systems
Scaling up EAs for very large databases
Parallel and/or distributed EAs for KDD tasks
Application to real-life databases (e.g., biological databases,
scientific databases, image databases)

Papers on other topics (not listed above) related to applications
of EAs to KDD process are also welcome.

Important dates:

Manuscript submission: August 31, 2002
Notification of review reports for revision (if any): December 31,
2002
Final version submission: February 28, 2003
Publication of the issue: as per IEEE-TEC schedule

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Alex A. Freitas, Ph.D.
PUCPR (Pontificia Universidade Catolica do Parana)
PPGIA - CCET
Rua Imaculada Conceicao, 1155
Curitiba - PR, 80215-901
Brasil
alex@...
http://www.ppgia.pucpr.br/~alex
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