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Leveraging Lexical Substitutes for Unsupervised Word Sense Induction (CROSBI ID 658223)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Alagić, Domagoj ; Šnajder, Jan ; Padó, Sebastian Leveraging Lexical Substitutes for Unsupervised Word Sense Induction // Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18). 2018. str. 5004-5011

Podaci o odgovornosti

Alagić, Domagoj ; Šnajder, Jan ; Padó, Sebastian

engleski

Leveraging Lexical Substitutes for Unsupervised Word Sense Induction

Word sense induction is the most prominent unsupervised approach to lexical disambiguation. It clusters word instances, typically represented by their bag-of-words contexts. Therefore, uninformative and ambiguous contexts present a major challenge. In this paper, we investigate the use of an alternative instance representation based on lexical substitutes, i.e., contextually suitable, meaning-preserving replacements. Using lexical substitutes predicted by a state- of-the-art automatic system and a simple clustering algorithm, we out-perform bag-of- words instance representations and compete with much more complex structured probabilistic models. Furthermore, we show that an oracle based on manually-labeled lexical substitutes yields yet substantially higher performance. Taken together, this provides evidence for a complementarity between word sense induction and lexical substitution that has not been given much consideration before.

Lexical semantics ; Natural language processing ; Lexical substitution ; Polysemy ; Word sense induction

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Podaci o prilogu

5004-5011.

2018.

objavljeno

Podaci o matičnoj publikaciji

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence (AAAI-18)

Podaci o skupu

32nd AAAI Conference on Artificial Intelligence (AAAI-18)

predavanje

02.02.2018-07.02.2018

New Orleans (LA), Sjedinjene Američke Države

Povezanost rada

Računarstvo, Informacijske i komunikacijske znanosti