TY - GEN
T1 - Evaluating vector space models using human semantic priming results
AU - Ettinger, Allyson
AU - Linzen, Tal
N1 - Publisher Copyright:
© 2016 Proceedings of the Annual Meeting of the Association for Computational Linguistics. All Rights Reserved.
PY - 2016
Y1 - 2016
N2 - Vector space models of word representation are often evaluated using human similarity ratings. Those ratings are elicited in explicit tasks and have well-known subjective biases. As an alternative, we propose evaluating vector spaces using implicit cognitive measures. We focus in particular on semantic priming, exploring the strengths and limitations of existing datasets, and propose ways in which those datasets can be improved.
AB - Vector space models of word representation are often evaluated using human similarity ratings. Those ratings are elicited in explicit tasks and have well-known subjective biases. As an alternative, we propose evaluating vector spaces using implicit cognitive measures. We focus in particular on semantic priming, exploring the strengths and limitations of existing datasets, and propose ways in which those datasets can be improved.
UR - http://www.scopus.com/inward/record.url?scp=85028695949&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85028695949&partnerID=8YFLogxK
U2 - 10.18653/v1/w16-2513
DO - 10.18653/v1/w16-2513
M3 - Conference contribution
AN - SCOPUS:85028695949
T3 - Proceedings of the Annual Meeting of the Association for Computational Linguistics
SP - 72
EP - 77
BT - Proceedings 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
PB - Association for Computational Linguistics (ACL)
T2 - 1st Workshop on Evaluating Vector-Space Representations for NLP, RepEval 2016 at the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016
Y2 - 7 August 2016
ER -