On-the-fly ontology matching in smart spaces: a multi-model approach
作者： Alexander Smirnov , Alexey Kashevnik , Nikolay Shilov , Sergey Balandin , Ian Oliver
DOI: 10.1007/978-3-642-14891-0_7
关键词:
摘要: Proper functioning of smart spaces demands semantic interoperability between knowledge processors connected to it. As a consequence it is required develop models that would enable translate on-the-fly the internal and space ontologies. This paper presents developed multi-model approach above problem, where major elements selected are described in detail.
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S. Montanelli, S. Castano, A. Ferrara, H-match: an algorithm for dynamically matching ontologies in peer-based systems international semantic web conference. pp. 218- 237 ,(2003)
George Wells, Coordination Languages: Back to the Future with Linda ,(2005)
Eduard Hovy, Combining and standardizing large- scale, practical ontologies for machine tranlation and other uses language resources and evaluation. pp. 535- 542 ,(1998)
Cosmin Stroe, Isabel F. Cruz, Flavio Palandri Antonelli, Efficient selection of mappings and automatic quality-driven combination of matching methods international conference on ontology matching. pp. 49- 60 ,(2009)
Frank van Harmelen, Steffen Staab, Rudi Studer, Simon Marta, Christiaan Fluit, Handbook on Ontologies in Information Systems ,(2003)
Yuzhong Qu, Yanbing Wang, Ningsheng Jian, Wei Hu, GMO: A Graph Matching for Ontologies. Integrating Ontologies. ,(2005)
Ondřej Šváb-Zamazal, Christian Meilicke, Heiner Stuckenschmidt, Dominique Ritze, A pattern-based ontology matching approach for detecting complex correspondences international conference on ontology matching. pp. 25- 36 ,(2009)
Mark A. Musen, Natalya Fridman, SMART: Automated Support for Ontology Merging and Alignment ,(1999)
Aliaksandr Autayeu, Vincenzo Maltese, Fausto Giunchiglia, Computing minimal mappings international conference on ontology matching. pp. 37- 48 ,(2009)
Deborah L. McGuinness, James Rice, Richard Fikes, Steve Wilder, An environment for merging and testing large ontologies principles of knowledge representation and reasoning. pp. 483- 493 ,(2000)