Soft Computing for Information Mining
A Workshop to be held at the
27th German Conference on Artificial Intelligence,
Aims and Scope of the Workshop
Efficient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the capability of computers to search huge amounts of data in a fast and effective manner. More often than not, however, the data to be analyzed is imprecise and afflicted with uncertainty. In the case of heterogeneous data sources such as text and video, the data might moreover be ambiguous and partly conflicting. Besides, patterns and relationships of interest are usually vague and match with the data at best approximately.
Thus, in order to make the information mining process more robust or, say, “human-like”, methods for searching and learning are needed that are tolerant toward imprecision, uncertainty, and exceptions, have approximate reasoning capabilities and are capable of handling partial truth. Properties of the aforementioned kind are typical of “soft computing”, a collection of methodologies whose cornerstones are fuzzy logic, neural networks, and evolutionary algorithms.
The workshop will focus on the support of the information mining process by methods from soft computing, including the main constituents fuzzy logic, neural networks, evolutionary algorithms and their hybrids as well as related methodologies such as, e.g., rough set theory or probabilistic and evidential reasoning. Topics of interest include but are not limited to the use of such techniques in data preprocessing, handling of incomplete and heterogeneous data, information mining methods (association analysis, classification and prediction, clustering, regression, outlier analysis, ...), interactive and online information mining, mining at multiple levels of abstraction, the incorporation of background knowledge, database querying and ad hoc information mining, visualization and presentation of information mining results.
Theoretical, methodological and application-oriented contributions are equally welcome. Selected papers will be published in the form of a special issue of the journal “Soft Computing”.
Potential authors are invited to submit an extended abstract of 2-4 pages detailing the problem under consideration, the methods that have been used, and the results that have been obtained. Please send abstracts in electronic form to Eyke Hüllermeier (see contact below).
Deadline for submissions (extended abstracts):
Eyke Hüllermeier, FB Mathematik und Informatik, Philipps-Universität Marburg, Lahnberge, D-35032 Marburg, firstname.lastname@example.org
Eyke Hüllermeier, FB Mathematik und Informatik, Philipps-Universität
Frank Klawonn, Department of Computer Science,
Rudolf Kruse, Department of Computer Science,
Ralf Mikut, Institute for Applied Computer Science, Forschungszentrum Karlsruhe GmbH
Thomas Runkler, Siemens AG, München