Over the last two decades, determining the similarity between words as well as between their meanings, that is, word senses, has been proven to be of vital importance in the field of Natural Language Processing. This paper provides the reader with an introduction to the tasks of computing word and sense similarity. These consist in computing the degree of semantic likeness between words and senses, respectively. First, we distinguish between two major approaches: the knowledge-based approaches and the distributional approaches. Second, we detail the representations and measures employed for computing similarity. We then illustrate the evaluation settings available in the literature and, finally, discuss suggestions for future research.

An overview of word and sense similarity / Navigli, R.; Martelli, F.. - In: NATURAL LANGUAGE ENGINEERING. - ISSN 1351-3249. - 25:6(2019), pp. 693-714. [10.1017/S1351324919000305]

An overview of word and sense similarity

Navigli R.;Martelli F.
2019

Abstract

Over the last two decades, determining the similarity between words as well as between their meanings, that is, word senses, has been proven to be of vital importance in the field of Natural Language Processing. This paper provides the reader with an introduction to the tasks of computing word and sense similarity. These consist in computing the degree of semantic likeness between words and senses, respectively. First, we distinguish between two major approaches: the knowledge-based approaches and the distributional approaches. Second, we detail the representations and measures employed for computing similarity. We then illustrate the evaluation settings available in the literature and, finally, discuss suggestions for future research.
2019
distributional semantics; knowledge-based similarity; semantic similarity; sense similarity; word similarity
01 Pubblicazione su rivista::01a Articolo in rivista
An overview of word and sense similarity / Navigli, R.; Martelli, F.. - In: NATURAL LANGUAGE ENGINEERING. - ISSN 1351-3249. - 25:6(2019), pp. 693-714. [10.1017/S1351324919000305]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1366657
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