More and more authors have realized that the lack of systematic methods and formal techniques for the design, the evaluation and the refinement are often important reasons for not using AI systems in practice. The first contributions in this field were limited to classical AI systems. Actually, more and more papers regarding non-classical types of systems (like case-based systems, e.g.), knowledge processing principles (learning principles, e.g.), and intelligent behavior are published.
EUDeris aims to cover the complete life-cycle of Knowledge Systems, i.e. their development, maintenance, evaluation, and refinement.
The objective of the special track is to focus on the contributions in these fields and to provide an environment for communicating different paradigms and approaches, thus hopefully stimulating future cooperation and synergistic activities.
The track will host any contributions to design, evaluate and refine intelligent systems.
Possible fields of related papers are:
Principles in knowledge systems and ontology design
Detecting and handling inconsistencies and other anomalies within knowledge bases
Fundamentals and formal methods for verification of AI systems
Fundamentals and formal methods and techniques of validity assessment of AI systems, AI principles, and intelligent behavior in general
Special approaches to verify and/or validate certain kinds of AI systems: rule-based, case-based, …
Special approaches or tools to evaluate systems of a particular application field
Knowledge base refinement by using the results of evaluation
Development and evaluation of ontologies
Maintenance and evolution of knowledge systems and ontologies
Methods for the evaluation of distributed knowledge bases
Evaluation of semi-formal knowledge bases
Problems in system certification and quality management
Extended abstracts (~2-6 pages), preferably in Springer LNCS (or plain (LaTeX) article) format should be submitted by October, 26th, 2008 to atzmueller@informatik.uni-wuerzburg.de.
List of submitted papers/titles:
Martin Atzmueller, Stephanie Beer, Alexander Hörnlein, Ralf Melcher, Hardi Lührs, Frank Puppe:
Design and Implementation of a Data Warehouse for Quality Management, System Evaluation and Knowledge Discovery in the Medical Domain [
Extended Abstract]
Martin Atzmueller, Alexander Hörnlein:
Exploiting the Power of Social Tagging Systems: A Semantic Flickr Approach for Tutoring and Knowledge Management [
Extended Abstract]
Joachim Baumeister:
Advanced Measures for Empirical Testing [
Abstract]
Joachim Baumeister, Grzegorz J. Nalepa:
On Verification of Distributed Knowledge Bases in Wikis [
Draft]
Rainer Knauf:
Knowledge Engineering with Didactic Knowledge. First Steps towards an Ultimate Goal [
Extended Abstract]
Grzegorz J. Nalepa:
XTT Rule Design and Implementation with Object-Oriented Methods [
Abstract]
Grzegorz J. Nalepa and Antoni Ligęza:
On ALSV Rules Inference Engine Design [
Abstract]