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Evaluation of Greek word embeddings

  • Athens Univ. of Econ. and Business
  • Ecole polytechnique

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Résumé

Since word embeddings have been the most popular input for many NLP tasks, evaluating their quality is critical. Most research efforts are focusing on English word embeddings. This paper addresses the problem of training and evaluating such models for the Greek language. We present a new word analogy test set considering the original English Word2vec analogy test set and some specific linguistic aspects of the Greek language as well. Moreover, we create a Greek version of WordSim353 test collection for a basic evaluation of word similarities. Produced resources are available for download. We test seven word vector models and our evaluation shows that we are able to create meaningful representations. Last, we discover that the morphological complexity of the Greek language and polysemy can influence the quality of the resulting word embeddings.

langue originaleAnglais
titreLREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings
rédacteurs en chefNicoletta Calzolari, Frederic Bechet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Helene Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
EditeurEuropean Language Resources Association (ELRA)
Pages2543-2551
Nombre de pages9
ISBN (Electronique)9791095546344
étatPublié - 1 janv. 2020
Evénement12th International Conference on Language Resources and Evaluation, LREC 2020 - Marseille, France
Durée: 11 mai 202016 mai 2020

Série de publications

NomLREC 2020 - 12th International Conference on Language Resources and Evaluation, Conference Proceedings

Une conférence

Une conférence12th International Conference on Language Resources and Evaluation, LREC 2020
Pays/TerritoireFrance
La villeMarseille
période11/05/2016/05/20

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