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Artificial Intelligence
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Communications of the ACM
Conceptual Spaces: The Geometry of Thought
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Hybrid model for semantic similarity measurement
OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems: CoopIS, COA, and ODBASE - Volume Part II
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GeoS'05 Proceedings of the First international conference on GeoSpatial Semantics
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GeoS'05 Proceedings of the First international conference on GeoSpatial Semantics
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International Journal of Geographical Information Science - Digital Gazetteer Research
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OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part II
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Acquisition and semantic annotation of data are fundamental tasks within the domain of cultural heritage. With the increasing amount of available data and ad hoc cross linking between their providers and users (e.g. through web services), data integration and knowledge refinement becomes even more important. To integrate information from several sources it has to be guaranteed that objects of discourse (which may be artifacts, events, persons, places or periods) refer to the same real world phenomena within all involved data sources. Local (database) identifiers however only disambiguate internal data, but fail in establishing connections to/between external data, while global identifiers can only partially solve this problem. Software assistants should support users in establishing such connections by delivering identity assumptions, i.e. by estimating whether examined data actually concerns the same real word phenomenon. This paper points out how similarity measures can act as groundwork for such assistants by introducing a similarity-based identity assumption assistant for historical places to support scholars in establishing links between distributed historical knowledge.