Volltext-Downloads (blau) und Frontdoor-Views (grau)
(Leider keine statistischen Daten vom 26.05. – 18.06.2018)
  • search hit 1 of 1
Back to Result List

Predicting Word Concreteness and Imagery

  • Concreteness of words has been studied extensively in psycholinguistic literature. A number of datasets have been created with average values for perceived concreteness of words. We show that we can train a regression model on these data, using word embeddings and morphological features, that can predict these concreteness values with high accuracy. We evaluate the model on 7 publicly available datasets. Only for a few small subsets of these datasets prediction of concreteness values are found in the literature. Our results clearly outperform the reported results for these datasets.

Download full text files

Export metadata

Statistics

frontdoor_oas
Metadaten
Author:Jean CharbonnierORCiD, Christian WartenaORCiDGND
URN:urn:nbn:de:bsz:960-opus4-13591
URL:https://www.aclweb.org/anthology/W19-0415
DOI:https://doi.org/10.25968/opus-1359
Parent Title (English):Proceedings of the 13th International Conference on Computational Semantics - Long Papers
Publisher:Association for Computational Linguistics
Place of publication:Stroudsburg, Pennsylvania
Editor:Simon Dobnik, Stergios Chatzikyriakidis, Vera Demberg
Document Type:Conference Proceeding
Language:English
Year of Completion:2019
Publishing Institution:Hochschule Hannover
Release Date:2019/07/23
Tag:Concreteness; Distributional Semantics; Imagery; Lexical Semantics
GND Keyword:Konkretum <Linguistik>
First Page:176
Last Page:187
Institutes:Fakultät III - Medien, Information und Design
DDC classes:020 Bibliotheks- und Informationswissenschaft
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International