2017 IJCNLP IJCNLP 2017

Integrating Vision and Language Datasets to Measure Word Concreteness

Abstract

AbstractWe present and take advantage of the inherent visualizability properties of words in visual corpora (the textual components of vision-language datasets) to compute concreteness scores for words. Our simple method does not require hand-annotated concreteness score lists for training, and yields state-of-the-art results when evaluated against concreteness scores lists and previously derived scores, as well as when used for metaphor detection.

🧭 Keyword Pioneer — word concreteness
🐝 Cross-Pollinator — Artificial Intelligence, Computer Vision, Deep Learning, Interdisciplinary, Machine Learning, Natural Language Processing