Learning to map between ontologies on the semantic web
Proceedings of the 11th international conference on World Wide Web
Toward the semantic geospatial web
Proceedings of the 10th ACM international symposium on Advances in geographic information systems
Determining Semantic Similarity among Entity Classes from Different Ontologies
IEEE Transactions on Knowledge and Data Engineering
A Formal Ontology of Properties
EKAW '00 Proceedings of the 12th European Workshop on Knowledge Acquisition, Modeling and Management
Representing and reasoning about semantic conflicts in heterogeneous information systems
Representing and reasoning about semantic conflicts in heterogeneous information systems
Exploring the Geospatial Semantic Web with DBpedia Mobile
Web Semantics: Science, Services and Agents on the World Wide Web
A mismatch description language for conceptual schema mapping and its cartographic representation
GIScience'10 Proceedings of the 6th international conference on Geographic information science
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Geospatial domain is characterised by vagueness, especially in the semantic disambiguation of the concepts in the domain, which makes defining universally accepted geo- ontology an onerous task. This is compounded by the lack of appropriate methods and techniques where the individual semantic conceptualisations can be captured and compared to each other. With multiple user conceptualisations, efforts towards a reliable Geospatial Semantic Web, therefore, require personalisation where user diversity can be incorporated. In this paper, a formal approach for detecting mismatches between a user's and an expert's conceptual model is outlined. The formalisation is used as the basis to develop algorithms to compare models defined in OWL. The algorithms are illustrated in a geographical domain using concepts from the SPACE ontology, and are evaluated by comparing test cases of possible user misconceptions. The work presented in this paper is part of our ongoing research on applying commonsense reasoning to elicit and maintain models that represent users' conceptualisations. Such user models will enable taking into account the users' perspective of the real world and will empower personalisation algorithms for the Semantic Web.