Abstract
Desktop search tools are becoming more popular; they allow full text searches using inverted indexes. Yet, the amount of locally stored data that they have to deal with is increasing rapidly. A different approach is to analyze the semantic relationships among collected data and thus preprocess the data semantically. The goal is to allow searches based on relationships among various objects rather than focusing on objects’ names. This would allow for searches far more sophisticated than those based on full text analysis. We introduce a database architecture based on an existing software prototype that is capable of meeting the various demands of a semantic information manager. This architecture is also capable of storing and querying RDF and RDF schemata. Moreover, RDF is used as a key part of the technology. Therefore, in this scenario, RDF is used not only to enrich the Web with machine-processable semantics, but also to incorporate it into a kind of Semantic Desktop Search Engine. In this paper, we describe the underlying technology of this research project.
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Weippl, E.R., Klemen, M., Fenz, S., Ekelhart, A., Tjoa, A.M. (2007). The Semantic Desktop: A Semantic Personal Information Management System Based on RDF and Topic Maps. In: Collard, M. (eds) Ontologies-Based Databases and Information Systems. ODBIS ODBIS 2006 2005. Lecture Notes in Computer Science, vol 4623. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75474-9_9
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DOI: https://doi.org/10.1007/978-3-540-75474-9_9
Publisher Name: Springer, Berlin, Heidelberg
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