Abstract
Context-based applications are supposed to decrease human-machine interactions. To this end, they must interpret the meaning of context data. Ontologies are a commonly accepted approach of specifying data semantics and are thus considered a precondition for the implementation of context-based systems. Yet, experiences gained from the European project Daidalos evoke concerns that this approach has its flaws when the application domain can hardly be delimited. These concerns are raised by the human limitation in dealing with complex specifications.
This paper proposes a relaxation of the situation: Humans strength is the understating of natural languages, computers, however, possess superior pattern matching power. Therefore, it is suggested to enrich or even replace semantic specifications of context data items by free-text descriptions. For instance, rather than using an Ontology specification to describe an Italian restaurant the restaurant can simply be described by its menu card.
To facilitate this methodology, context documents are introduced and a novel information retrieval approach is elucidated, evaluated, and analysed with the help of Bose-Einstein statistics. It is demonstrated that the new approach clearly outperforms conventional information retrieval engines and is an excellent addition to context Ontologies.
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Pils, C., Roussaki, I., Strimpakou, M. (2006). Location-Based Context Retrieval and Filtering. In: Hazas, M., Krumm, J., Strang, T. (eds) Location- and Context-Awareness. LoCA 2006. Lecture Notes in Computer Science, vol 3987. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11752967_17
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DOI: https://doi.org/10.1007/11752967_17
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