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Conference Papers Year : 2017

Turning Distributional Thesauri into Word Vectors for Synonym Extraction and Expansion

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Abstract

In this article, we propose to investigate a new problem consisting in turning a distributional thesaurus into dense word vectors. We propose more precisely a method for performing such task by associating graph embedding and distributed representation adaptation. We have applied and evaluated it for English nouns at a large scale about its ability to retrieve synonyms. In this context, we have also illustrated the interest of the developed method for three different tasks: the improvement of already existing word embeddings, the fusion of heterogeneous representations and the expansion of synsets
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Dates and versions

cea-01857883 , version 1 (17-08-2018)

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  • HAL Id : cea-01857883 , version 1

Cite

Olivier Ferret. Turning Distributional Thesauri into Word Vectors for Synonym Extraction and Expansion. Eighth International Joint Conference on Natural Language Processing (IJCNLP 2017), Nov 2017, Taipei, Taiwan. pp.273-283. ⟨cea-01857883⟩
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