SAM: A tool for the semi-automatic mapping and enrichment of ontologies

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Abstract

Ontologies are fundamental tools used with different purposes and with different modalities in different areas and communities. To guarantee the right level of quality, the most widely used ontologies are man-made. However, developing and maintaining them turns out to be extremely time-consuming. For this reason, there are approaches aiming at their automatic construction where ontologies are incrementally extended by extracting and integrating knowledge from existing sources. However, these approaches tend to reach an accuracy that, according to the application they need to serve, cannot be always considered satisfactory. Therefore, when a higher accuracy is necessary, manual or semi-automatic approaches are still preferable. In this paper we present a technique and a corresponding tool, that we called SAM (semi-automatic mapper), for the semi-automatic enrichment of an ontology through the mapping of an external source to the target ontology. As proved by our evaluation, the tool allows saving around 50% of the time required by purely manual approaches. © 2012 Springer-Verlag.

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APA

Maltese, V., & Hossain, B. A. (2012). SAM: A tool for the semi-automatic mapping and enrichment of ontologies. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7567 LNCS, pp. 454–463). https://doi.org/10.1007/978-3-642-33618-8_61

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