Opinion Mining by Convolutional Neural Networks for Maximizing Discoverability of Nanomaterials-Reference-Cited by-同舟云学术

Opinion Mining by Convolutional Neural Networks for Maximizing Discoverability of Nanomaterials

Published:2023-11-20 Issue: Volume: Page:
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Xie Tong¹²^ORCID,Wan Yuwei³²,Wang Haoran¹,Østrøm Ina¹^ORCID,Wang Shaozhou¹²^ORCID,He Mingrui¹,Deng Rong¹^ORCID,Wu Xinyuan¹,Grazian Clara⁴⁵,Kit Chunyu³,Hoex Bram¹^ORCID

Affiliation:

1. School of Photovoltaic and Renewable Energy Engineering, University of New South Wales, Kensington, NSW 2052, Australia

2. GreenDynamics Pty. Ltd., Kensington, NSW 2052, Australia

3. Department of Linguistics and Translation, City University of Hong Kong, 83 Tat Chee Ave, Kowloon Tong, Hong Kong

4. DARE ARC Training Centre in Data Analytics for Resources and Environments, South Eveleigh, NSW 2015, Australia

5. School of Mathematics and Statistics, University of Sydney, Camperdown, NSW 2006, Australia

Funder

Australian Centre for Advanced Photovoltaics

Publisher

American Chemical Society (ACS)

Subject

Library and Information Sciences,Computer Science Applications,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.3c00746

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