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Erschienen in:
2005 | OriginalPaper | Buchkapitel
Using the Structure of a Conceptual Network in Computing Semantic Relatedness
verfasst von : Iryna Gurevych
Erschienen in: Natural Language Processing – IJCNLP 2005
Verlag: Springer Berlin Heidelberg
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We present a new method for computing semantic relatedness of concepts. The method relies solely on the structure of a conceptual network and eliminates the need for performing additional corpus analysis. The network structure is employed to generate artificial conceptual glosses. They replace textual definitions
proper
written by humans and are processed by a dictionary based metric of semantic relatedness [1]. We implemented the metric on the basis of GermaNet, the German counterpart of WordNet, and evaluated the results on a German dataset of 57 word pairs rated by human subjects for their semantic relatedness. Our approach can be easily applied to compute semantic relatedness based on alternative conceptual networks, e.g. in the domain of life sciences.