Abstract
We present a demo of SCARLET, a technique for discovering relations between two concepts by harvesting the Semantic Web, i.e., automatically finding and exploring multiple and heterogeneous online ontologies. While we have primarily used SCARLET's relation discovery functionality to support ontology matching and enrichment tasks, it is also available as a stand alone component that can potentially be integrated in a wide range of applications. This demo will focus on presenting SCARLET's functionality and its different parametric settings that can influence the trade-off between its accuracy and time performance. © 2008 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Sabou, M., D’Aquin, M., & Motta, E. (2008). SCARLET: SemantiC relation discovery by harvesting OnLinE onTologies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5021 LNCS, pp. 854–858). https://doi.org/10.1007/978-3-540-68234-9_72
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