Information-flow-based ontology mapping

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Abstract

As ontologies become ever more important for semantically-rich information exchange and a crucial element for supporting knowledge sharing in a large distributed environment, like the Web, the demand for sharing them increases accordingly. One way of achieving this ambitious goal is to provide mechanised ways for mapping and merging ontologies. This has been the focus of recent research in knowledge engineering. However, we observe a dearth of mapping methods that are based on a strong theoretical ground, are easy to replicate in different settings, and use semantically-rich mechanisms for performing ontology mapping. In this paper, we aim to fill in these gaps with a method we propose for Information-Flow-based ontology mapping. Our method draws on the proven theoretical ground of Information Flow and channel theory, and we provide a systematic and mechanised methodology for deploying it on a distributed environment to perform ontology mapping among a variety of different ontologies. We applied our method at a large-scale experiment of mapping five ontologies modelling Computer Science departments in five UK Universities. We elaborate on a theory for ontology mapping, analyse the mechanised steps of applying it, and assess its ontology mapping results. © Springer-Verlag Berlin Heidelberg 2002.

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APA

Kalfoglou, Y., & Schorlemmer, M. (2002). Information-flow-based ontology mapping. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2519 LNCS, pp. 1132–1151). Springer Verlag. https://doi.org/10.1007/3-540-36124-3_72

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