ChEMU 2020: Natural Language Processing Methods Are Effective for Information Extraction From Chemical Patents

ChEMU 2020: Natural Language Processing Methods Are Effective for Information Extraction From Chemical Patents

Chemical patents represent a valuable source of information about new chemical compounds, which is critical to the drug discovery process. Automated information extraction over chemical patents is, however, a challenging task due to the large volume of existing patents and the complex linguistic pro...

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Bibliographic Details
Main Authors: Jiayuan He, Dat Quoc Nguyen, Saber A. Akhondi, Christian Druckenbrodt, Camilo Thorne, Ralph Hoessel, Zubair Afzal, Zenan Zhai, Biaoyan Fang, Hiyori Yoshikawa, Ameer Albahem, Lawrence Cavedon, Trevor Cohn, Timothy Baldwin, Karin Verspoor
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-03-01
Series:Frontiers in Research Metrics and Analytics
Subjects:
named entity recognition
event extraction
information extraction
chemical reactions
patent text mining
cheminformatics
Online Access:https://www.frontiersin.org/articles/10.3389/frma.2021.654438/full

Internet

https://www.frontiersin.org/articles/10.3389/frma.2021.654438/full

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