Medical Synonym Extraction with Concept Space Models
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 989-994.
Abstract
In this paper, we present a novel approach for medical synonym extraction. We aim to integrate the term embedding with the medical domain knowledge for healthcare applications. One advantage of our method is that it is very scalable. Experiments on a dataset with more than 1M term pairs show that the proposed approach outperforms the baseline approaches by a large margin.
Chang Wang, Liangliang Cao, and Bowen Zhou. 2015. Medical Synonym Extraction with Concept Space Models. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15. IJCAI, 989–994. https://ijcai.org/proceedings/2015/144
Wang, C., Cao, L., & Zhou, B. (2015). Medical Synonym Extraction with Concept Space Models. In Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 (pp. 989–994). IJCAI. https://ijcai.org/proceedings/2015/144
@inproceedings{ijcai2015p144,
title = {Medical Synonym Extraction with Concept Space Models},
author = {Wang, Chang and Cao, Liangliang and Zhou, Bowen},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {989--994},
year = {2015},
month = {7},
note = {Main Track},
url = {https://ijcai.org/proceedings/2015/144},
}
TY - CPAPER TI - Medical Synonym Extraction with Concept Space Models AU - Wang, Chang AU - Cao, Liangliang AU - Zhou, Bowen T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 989 EP - 994 UR - https://ijcai.org/proceedings/2015/144 ER -Copied
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