Integrating the IAC neural network in ontology mapping

Ontology mapping seeks to find semantic correspondences between similar elements of different ontologies. This paper proposes a neural network based approach to search for a global optimal solution that best satisfies ontology constraints. Experiments on OAEI benchmark tests show it dramatically improves the performance of preliminary mapping results. Categories and Subject Descriptors D.2.12 [Software Engineering]: Interoperability ? Data mapping; I.2.6 [Artificial Intelligence]: Learning ? Connectionism and neural nets. General Terms Algorithms, Design, Experimentation. Keywords ontology mapping, interactive activation and competition (IAC) neural network, constraint satisfaction problem (CSP), PRIOR+

• Type: Conference
• Year: 2008
• Where: WWW
• Authors: Ming Mao, Yefei Peng, Michael Spring
• Keywords: Internet Technology, Keywords Ontology Mapping, Neural Network, Satisfies Ontology Constraints, WWW 2008