We propose a cluster analysis approach to quantify near-synonymy relations and compare non-parametric and parametric methods. The first approach is model free since it does not assume an underlying model of lexical knowledge but it uncovers the group structure in the set of near-synonyms of a target word by comparing the list of synonyms of the given entry with those of its near-synonyms as contained into available thesauri. Then, in order to validate the results provided by the cluster analysis, a statistical model is introduced for analyzing human judgments of perceived degree of synonymy, also by a relationship with subjects’ characteristics. Empirical evidence for a selected word of Italian is presented and discussed.

Grouping near-synonyms of a dictionary entry: thesauri and perceptions

CAPPELLI, CARMELA
2011

Abstract

We propose a cluster analysis approach to quantify near-synonymy relations and compare non-parametric and parametric methods. The first approach is model free since it does not assume an underlying model of lexical knowledge but it uncovers the group structure in the set of near-synonyms of a target word by comparing the list of synonyms of the given entry with those of its near-synonyms as contained into available thesauri. Then, in order to validate the results provided by the cluster analysis, a statistical model is introduced for analyzing human judgments of perceived degree of synonymy, also by a relationship with subjects’ characteristics. Empirical evidence for a selected word of Italian is presented and discussed.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11588/490874
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