Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
