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Evaluation by Association: A Systematic Study of Quantitative Word Association Evaluation
2017
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
Recent work on evaluating representation learning architectures in NLP has established a need for evaluation protocols based on subconscious cognitive measures rather than manually tailored intrinsic similarity and relatedness tasks. In this work, we propose a novel evaluation framework that enables large-scale evaluation of such architectures in the free word association (WA) task, which is firmly grounded in cognitive theories of human semantic representation. This evaluation is facilitated
doi:10.18653/v1/e17-1016
dblp:conf/eacl/KorhonenVK17
fatcat:ckrjnytvhzautpyg2p5ueda3xe