An improved crowdsourcing based evaluation technique for word embedding methods

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

In this proposal track paper, we have presented a crowdsourcing-based word embedding evaluation technique that will be more reliable and linguistically justified. The method is designed for intrinsic evaluation and extends the approach proposed in (Schnabel et al., 2015). Our improved evaluation technique captures word relatedness based on the word context.

Original languageEnglish
Title of host publicationProceedings of the 1st Workshop on Evaluating Vector-Space Representations for NLP, RepEval 2016 at the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016
PublisherAssociation for Computational Linguistics (ACL)
Pages55-61
Number of pages7
ISBN (Electronic)9781945626142
Publication statusPublished - 2016
Event1st Workshop on Evaluating Vector-Space Representations for NLP, RepEval 2016 at the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Berlin, Germany
Duration: 7 Aug 2016 → …

Publication series

NameProceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN (Print)0736-587X

Conference

Conference1st Workshop on Evaluating Vector-Space Representations for NLP, RepEval 2016 at the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016
Country/TerritoryGermany
CityBerlin
Period7/08/16 → …

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