CFP

Fuzzy Sets and Systems
An International Journal in Information Science and Engineering

Special Issue on Fuzzy Sets in Knowledge Discovery

As a response to the progress in digital data acquisition and storage technology, along with the limited human capabilities in analyzing and exploiting large amounts of data, the field of knowledge discovery in databases (KDD) has recently emerged as a new research discipline, lying at the intersection of statistics, machine learning, data management, and other areas. According to a widely accepted definition, KDD refers to the non-trivial process of identifying valid, novel, potentially useful, and ultimately understandable structure in data. The central step within the overall KDD process is data mining, the application of computational techniques to the task of finding patterns and models in data. Still, KDD also involves further important steps, notably data preparation, data cleaning, incorporation of prior knowledge, and interpretation of data mining results.

Fuzzy sets have the potential to support all of the steps comprising the KDD process. Their capability to interface quantitative patterns with qualitative knowledge structures expressible in terms of natural language can considerably improve the comprehensibility of extracted patterns, which is a point of major importance in data mining. Fuzzy information granulation allows for trading off accuracy against efficiency and understandability of models. Amongst other things, fuzzy sets can also be useful in data reduction, in dealing with incomplete and heterogeneous data, in modeling prior knowledge, or in interactive data mining, where the mining process is under partial control of the analyst.

The focus of the special issue is on conceptual and methodological aspects of knowledge discovery. Prospective authors are invited to submit substantial, original and previously unpublished research showing how fuzzy set-based concepts and methods can contribute to KDD. Topics of interest include but are not limited to the application of fuzzy sets in

• data preprocessing,
• handling of incomplete and heterogeneous data,
• data mining methods (association analysis, classification and prediction, clustering, regression, outlier analysis, ...),
• interactive and online mining,
• mining at multiple levels of abstraction,
• the incorporation of background knowledge,
• database querying and ad hoc data mining,
• the presentation of data mining results.

Authors are invited to send an electronic version of their paper to the guest editor:
Eyke Hüllermeier
Department of Mathematics and Computer Science
University of Marburg
D-35032 Marburg
Hans-Meerwein-Str., Lahnberge
Germany
email: eyke@mathematik.uni-marburg.de or eyke@upb.de

Manuscrips should conform to the guidelines of the journal
(http://www.elsevier.com/locate/fss)
and should not exceed 20 pages in length. All submissions will undergo
the same review process
as do regular papers.

Schedule
Deadline for submissions: March 31, 2003
Acceptance notification: September 31, 2003
Final manuscripts: December 31, 2003