Discovering word senses from a network of lexical cooccurrences
By Olivier Ferret. 2004
44 citations recorded by the source corpus.
Lexico-semantic networks such as WordNet have been criticized about the nature of the senses they distinguish as well as on the way they define these senses. In this article, we present a possible solution to overcome these limits by defining the sense of words from the way they are used. More precisely, we propose to differentiate the senses of a word from a network of lexical cooccurrences built from a large corpus. This method was tested both for French and English and was evaluated for English by comparing its results with WordNet.
Subfields: Natural Language Processing
How researchers see this paper
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In Natural Language Processing
- Jure Leskovec
- William L. Hamilton
- Dan Jurafsky
- Luke S. Zettlemoyer
- Noah A. Smith
- Kyunghyun Cho
- Hannaneh Hajishirzi
- Mohit Bansal
Citations in the corpus
- Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change (2016, methodology): “Variants of this measure are often used in word-sense discrimination and correlate with, e.g., number of senses in WordNet (Dorow and Widdows, 2003; Ferret, 2004).”