Analysis of Single-Objective and Multi-Objective Evolutionary Algorithms in Keyword Cluster Optimization
V. Dorfer, S. M. Winkler, T. Kern, G. Petz, P. Faschang - Analysis of Single-Objective and Multi-Objective Evolutionary Algorithms in Keyword Cluster Optimization - Proceedings of International Conference on Computer Aided Systems Theory EUROCAST 2011, Las Palmas, Spanien, 2011, pp. 3
As it is not trivial to cope with the fast growing number of papers published in the field of medicine and biology, intelligent search strategies are needed to be able to access the required information as fast and accurately as possible. In  we have proposed a method for keyword clustering as a first step towards an intelligent search strategy in biomedical information retrieval. In this paper we focus on the analysis of the application of evolutionary algorithms to solve this keyword clustering optimization problem; the results obtained using genetic algorithms and evolution strategies are discussed, and we also analyze the internal dynamics of the algorithms applied here using solution encoding specific population diversity analysis, which is also defined in this paper.
- FH-Prof. Mag. Dr. Gerald Petz
- DI (FH) Viktoria Dorfer MSc
- FH-Prof. DI Dr. Stephan Winkler
- DI (FH) Thomas Kern
- Patrizia Faschang B.A.
- Fakultät für Informatik, Kommunikation und Medien, Hagenberg
- Fakultät für Management, Steyr
- Research Center Hagenberg
- Research Center Steyr
- Research Group Bioinformatik