An Improved Ant Colony Optimization for Ontology Matching
The Hungarian algorithm used in ontology matching sometimes cannot get the solution since this algorithm does not converge when dealing with special data. In order to solve this problem, this paper presents an improved ant colony optimization for ontology matching problem (ACOM). We utilize many kinds of rating functions which are also called base matchers to evaluate the distance of two ontology entries. After getting the distance matrix of ontology entries, we use an improved ant colony optimization algorithm to extract the best alignment instead of using the traditional Hungarian method. Finally, a set of experiments are conducted to analysis and evaluate the performance of ACOM in solving ontology matching problem. We use Ontology Alignment Evaluation Initiative (OAEI) benchmark test suite with pairs of ontologies as test cases and compare our results with three algorithms presented in the OAEI 2008. The results of experiments show that our system has a good performance in the ontology matching process.
semantic web ontology matching ant colony algorithm
Xiaoyun Wang Qiyu Xu
Institute of Management Science & Information Engineering Hangzhou Dianzi University Hangzhou,China
国际会议
上海
英文
234-238
2011-03-11（万方平台首次上网日期，不代表论文的发表时间）