Title :
GAOM: Genetic Algorithm Based Ontology Matching
Author :
Wang, Junli ; Ding, Zhijun ; Jiang, ChangJun
Author_Institution :
Dept. of Comput. Sci. & Eng., Tongji Univ., Shanghai
Abstract :
In this paper a genetic algorithm-based optimization procedure for ontology matching problem is presented as a feature-matching process. First, from a global view, we model the problem of ontology matching as an optimization problem of a mapping between two compared ontologies, and every ontology has its associated feature sets. Second, as a powerful heuristic search strategy, genetic algorithm is employed for the ontology matching problem. Given a certain mapping as optimizing object for GA, fitness function is defined as a global similarity measure function between two ontologies based on feature sets. Finally, a set of experiments are conducted to analysis and evaluate the performance of GA in solving ontology matching problem
Keywords :
feature extraction; genetic algorithms; ontologies (artificial intelligence); feature matching; fitness function; genetic algorithm; global similarity measure function; ontology matching; optimization; Computer science; Educational institutions; Genetic algorithms; Genetic engineering; Information science; Ontologies; Performance analysis; Semantic Web; Taxonomy; Virtual colonoscopy;
Conference_Titel :
Services Computing, 2006. APSCC '06. IEEE Asia-Pacific Conference on
Conference_Location :
Guangzhou, Guangdong
Print_ISBN :
0-7695-2751-5
DOI :
10.1109/APSCC.2006.59