{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,1]],"date-time":"2025-03-01T06:00:51Z","timestamp":1740808851555,"version":"3.38.0"},"reference-count":39,"publisher":"SAGE Publications","issue":"4","license":[{"start":{"date-parts":[[2009,3,24]],"date-time":"2009-03-24T00:00:00Z","timestamp":1237852800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Journal of Information Science"],"published-print":{"date-parts":[[2009,8]]},"abstract":" Ontology matching aims to find semantic correspondences between a pair of input ontologies. A number of matching techniques have been proposed recently. We may, however, benefit more from a combination of such techniques as opposed to just a single method. This is more appropriate, but very often the user has no prior knowledge about which technique is more suitable for the task at hand, and it remains a labour intensive and expensive task to perform. Further, the complexity of the matching process as well as the quality of the result is affected by the choice of the applied matching techniques. We study this problem and propose a framework for finding suitable matches. A main feature of this is that it improves the structure matching techniques and the end result accordingly. We have developed a running prototype of the proposed framework and conducted experiments to compare our results with existing techniques. While being comparable in efficiency, the experimental results indicate our proposed technique produces better quality matches. <\/jats:p>","DOI":"10.1177\/0165551508100383","type":"journal-article","created":{"date-parts":[[2009,3,25]],"date-time":"2009-03-25T02:18:20Z","timestamp":1237947500000},"page":"379-397","source":"Crossref","is-referenced-by-count":15,"title":["An empirical comparison of ontology matching techniques"],"prefix":"10.1177","volume":"35","author":[{"given":"Ahmed","family":"Alasoud","sequence":"first","affiliation":[{"name":"Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada"}]},{"given":"Volker","family":"Haarslev","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada"}]},{"given":"Nematollaah","family":"Shiri","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, Concordia University, Montreal, Quebec, Canada,"}]}],"member":"179","published-online":{"date-parts":[[2009,3,24]]},"reference":[{"key":"atypb1","doi-asserted-by":"publisher","DOI":"10.1007\/s10115-003-0137-2"},{"volume-title":"Proceedings of the 18th National Conference on Artificial Intelligence (AAAI)","author":"N. 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Li","key":"atypb26"},{"volume-title":"Proceedings of the Workshop on Meaning Coordination and Negotiation","author":"P. Mitra","key":"atypb27"},{"volume-title":"Proceedings of the International Workshop on Ontology Matching","author":"S. Massmann","key":"atypb28"},{"key":"atypb29","doi-asserted-by":"crossref","unstructured":"A. Doan, J. Madhavan, P. Domingos and A. Halevy, Ontology matching: A machine learning approach. In: S. Staab and R. Studer (eds), Handbook on Ontologies in Information Systems (Springer , Heildelberg, 2003, 397-416).","DOI":"10.1007\/978-3-540-24750-0_19"},{"volume-title":"Proceedings of the International Workshop on Ontology Matching (OM)","author":"W. Hu","key":"atypb30"},{"volume-title":"Proceedings of the 16th European Conference on Artificial Intelligence (ECAI-04)","author":"J. Euzenat","key":"atypb31"},{"volume-title":"Proceedings of the K-Cap Workshop on Integrating Ontologies","author":"W. 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