Publication Details

Deep Learning from Web-Scale Corpora for Better Dictionary Interfaces

OTRUSINA, L.; SMRŽ, P. Deep Learning from Web-Scale Corpora for Better Dictionary Interfaces. Proceedings of the 4th Workshop on Cognitive Aspects of the Lexicon (CogALex). Dublin: Association for Computational Linguistics, 2014. p. 22-30. ISBN: 978-1-63439-217-4.
Czech title
Deep Learning z webových korpusů pro lepší rozhraní ke slovníkům
Type
conference paper
Language
English
Authors
URL
Keywords

Word2Vec, neural networks, ClueWeb, UKWaC, tip-of-the-tongue phenomenon

Abstract

This paper explores advanced learning mechanisms - neural networks trained by the Word2Vec method - for predicting word associations. We discuss how the approach can be built into dictionary interfaces to help tip-of-the-tongue searches. We also describe our contribution to the CogALex 2014 shared task. We argue that the reverse response-stimulus word associations chosen for the shared task are only mildly related to the motivation idea of the lexical access support system. The methods employed in our contribution are briefly introduced. We present results of experiments with various parameter settings and show what improvement can be expected if more than one answer is allowed. The paper concludes with a proposal for a new collective effort to assemble real tip-of-the-tongue situation records for future, more-realistic evaluations.

Published
2014
Pages
22–30
Proceedings
Proceedings of the 4th Workshop on Cognitive Aspects of the Lexicon (CogALex)
ISBN
978-1-63439-217-4
Publisher
Association for Computational Linguistics
Place
Dublin
BibTeX
@inproceedings{BUT111643,
  author="Lubomír {Otrusina} and Pavel {Smrž}",
  title="Deep Learning from Web-Scale Corpora for Better Dictionary Interfaces",
  booktitle="Proceedings of the 4th Workshop on Cognitive Aspects of the Lexicon (CogALex)",
  year="2014",
  pages="22--30",
  publisher="Association for Computational Linguistics",
  address="Dublin",
  isbn="978-1-63439-217-4",
  url="http://www.aclweb.org/anthology/W/W14/W14-4703.pdf"
}
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