Paper: Using the Structure of a Conceptual Network in Computing Semantic Relatedness

ACL ID I05-1067
Title Using the Structure of a Conceptual Network in Computing Semantic Relatedness
Venue International Joint Conference on Natural Language Processing
Session Main Conference
Year 2005
Authors

We present a new method for computing semantic relatedness of con- cepts. The method relies solely on the structure of a conceptual network and eliminates the need for performing additional corpus analysis. The network struc- ture 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 re- latedness. Our approach can be easily applied to compute semantic relatedness based on alternative conceptual networks, e.g. in the domain of life sciences.