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Autor:
Matuschek, Michael; Miller, Tristan; Gurevych, Iryna:

Titel:
A language-independent sense clustering approach for enhanced WSD

Quelle:
In: Ruppenhofer, Josef;Faaß, Gertrud (Hrsg.): Proceedings of the12th edition of the Konvens Conference Hildesheim : Universitätsverlag Hildesheim (2014) , 11-21

URL des Volltextes:
http://nbn-resolving.de/urn:nbn:de:gbv:hil2-opus-2893

Sprache:
Englisch

Dokumenttyp:
4. Beiträge in Sammelwerken; Tagungsband/Konferenzbeitrag/Proceedings

Schlagwörter:
Computerlinguistik, Semantik, Sinn, Sprachwissenschaft, Wort, Wortschatz


Abstract(original):
We present a method for clustering word senses of a lexical-semantic resource by mapping them to those of another sense inventory. This is a promising way of reducing polysemy in sense inventories and consequently improving word sense disambiguation performance. In contrast to previous approaches, we use Dijkstra-WSA, a parameterizable alignment algorithm which is largely resource- and language-agnostic. To demonstrate this, we apply our technique to GermaNet, the German equivalent to WordNet. The Germa- Net sense clusterings we induce through alignments to various collaboratively constructed resources achieve a significant boost in accuracy, even though our method is far less complex and less dependent on language-specific knowledge than past approaches. (DIPF/Orig.)


DIPF-Abteilung:
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last modified Nov 11, 2016