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Autor*innen: Erbs, Nicolai; Gurevych, Iryna; Zesch, Torsten
Titel: Sense and similarity. A study of sense-level similarity measures
Aus: Bos, Johan; Frank, Anette; Navigli, Roberto (Hrsg.): Proceedings of the 3rd Joint Conference on Lexical and Computational Semantics (SEM 2014), Stroudsburg; PA: Association for Computational Linguistics, 2014 , S. 30-39
URL: http://www.aclweb.org/anthology/S14-1004
Dokumenttyp: 4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache: Englisch
Schlagwörter: Ambiguität; Begriff; Computerlinguistik; Messung; Semantik; Sinn; Textanalyse; Wort
Abstract: In this paper, we investigate the difference between word and sense similarity measures and present means to convert a state-of-the-art word similarity measure into a sense similarity measure. In order to evaluate the new measure, we create a special sense similarity dataset and re-rate an existing word similarity dataset using two different sense inventories from WordNet and Wikipedia. We discover that word-level measures were not able to differentiate between different senses of one word, while sense-level measures actually increase correlation when shifting to sense similarities. Sense-level similarity measures improve when evaluated with a re-rated sense-aware gold standard, while correlation with word-level similarity measures decreases. (DIPF/Org.)
DIPF-Abteilung: Informationszentrum Bildung