Exploring Diachronic Changes of Biomedical Knowledge using Distributed Concept Representations

Gaurav Vashisth, Jan-Niklas Voigt-Antons, Michael Mikhailov, Roland Roller


Abstract
In research best practices can change over time as new discoveries are made and novel methods are implemented. Scientific publications reporting about the latest facts and current state-of-the-art can be possibly outdated after some years or even proved to be false. A publication usually sheds light only on the knowledge of the period it has been published. Thus, the aspect of time can play an essential role in the reliability of the presented information. In Natural Language Processing many methods focus on information extraction from text, such as detecting entities and their relationship to each other. Those methods mostly focus on the facts presented in the text itself and not on the aspects of knowledge which changes over time. This work instead examines the evolution in biomedical knowledge over time using scientific literature in terms of diachronic change. Mainly the usage of temporal and distributional concept representations are explored and evaluated by a proof-of-concept.
Anthology ID:
W19-5037
Volume:
Proceedings of the 18th BioNLP Workshop and Shared Task
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Dina Demner-Fushman, Kevin Bretonnel Cohen, Sophia Ananiadou, Junichi Tsujii
Venue:
BioNLP
SIG:
SIGBIOMED
Publisher:
Association for Computational Linguistics
Note:
Pages:
348–358
Language:
URL:
https://aclanthology.org/W19-5037
DOI:
10.18653/v1/W19-5037
Bibkey:
Cite (ACL):
Gaurav Vashisth, Jan-Niklas Voigt-Antons, Michael Mikhailov, and Roland Roller. 2019. Exploring Diachronic Changes of Biomedical Knowledge using Distributed Concept Representations. In Proceedings of the 18th BioNLP Workshop and Shared Task, pages 348–358, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
Exploring Diachronic Changes of Biomedical Knowledge using Distributed Concept Representations (Vashisth et al., BioNLP 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-5037.pdf