@inproceedings{kehat-pustejovsky-2017-integrating,
title = "Integrating Vision and Language Datasets to Measure Word Concreteness",
author = "Kehat, Gitit and
Pustejovsky, James",
editor = "Kondrak, Greg and
Watanabe, Taro",
booktitle = "Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)",
month = nov,
year = "2017",
address = "Taipei, Taiwan",
publisher = "Asian Federation of Natural Language Processing",
url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/I17-2018/",
pages = "103--108",
abstract = "We 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."
}
Markdown (Informal)
[Integrating Vision and Language Datasets to Measure Word Concreteness](https://preview.aclanthology.org/jlcl-multiple-ingestion/I17-2018/) (Kehat & Pustejovsky, IJCNLP 2017)
ACL