Computing Semantic Relatedness of GermaNet Concepts

نویسندگان

  • Iryna Gurevych
  • Hendrik Niederlich
چکیده

We present a system designed to compute the semantic relatedness between a pair of GermaNet concepts (word senses). Five different metrics have been implemented. Three of them are information content based and incorporate the Two metrics constitute the application of a Lesk algorithm (Lesk 1986) to artificial conceptual glosses generated from GermaNet. We show that four metrics correlate very well with a set of human judgments of semantic relatedness. We conclude with implementation issues and a description of a graphical user interface to compute the semantic relatedness of German words. semantischen Beziehung zwischen Wortbedeutungen in GermaNet.

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تاریخ انتشار 2005