Abstract
The Semantic Web (SW) originally aims at studying a system interoperability based on a shared common knowledge base (ontology). Henceforth, the SW sets its heart on a semantic coordination of community parlance representative resources (in complement to a common knowledge base shared by the users). The matter is not only to use techniques to handle a large amount of data, but also to use approaches to keep the community parlance features. Thus, Web documents and folksonomies are the main semantic vehicle. They are little structured and Natural Language Processing (NLP) methods are then beneficial to analyze language specificities with a view to automating tasks about text. This paper describes a use of NLP techniques for the SW through a document engineering application: the information retrieval in a catalogue of online medical resources. Our approach emphasizes benefits of NLP techniques to handle multi-granular terminological resources.
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Lortal, G., Chaignaud, N., Kotowicz, JP., Pécuchet, JP. (2009). NLP Contribution to the Semantic Web: Linking the Term to the Concept. In: Velásquez, J.D., Ríos, S.A., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2009. Lecture Notes in Computer Science(), vol 5711. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04595-0_38
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