TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Charbonnier, Jean
A1  - Wartena, Christian
ED  - Dobnik, Simon
ED  - Chatzikyriakidis, Stergios
ED  - Demberg, Vera
T1  - Predicting Word Concreteness and Imagery
T2  - Proceedings of the 13th International Conference on Computational Semantics - Long Papers
N2  - 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.
KW  - Concreteness
KW  - Imagery
KW  - Distributional Semantics
KW  - Lexical Semantics
KW  - Konkretum <Linguistik>
Y1  - 2019
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:960-opus4-13591
UR  - https://www.aclweb.org/anthology/W19-0415
U6  - https://doi.org/10.25968/opus-1359
DO  - https://doi.org/10.25968/opus-1359
SP  - 176
EP  - 187
PB  - Association for Computational Linguistics
CY  - Stroudsburg, Pennsylvania
ER  -