Chinese Word Segmentation Based on Self‐Learning Model and Geological Knowledge for the Geoscience Domain-Reference-Cited by-同舟云学术

Chinese Word Segmentation Based on Self‐Learning Model and Geological Knowledge for the Geoscience Domain

Published:2021-06 Issue:6 Volume:8 Page:
ISSN:2333-5084
Container-title:Earth and Space Science
language:en
Short-container-title:Earth Space Sci

Author:

Li Wenjia¹²,Ma Kai³,Qiu Qinjun¹²^ORCID,Wu Liang¹²,Xie Zhong¹²,Li Sanfeng⁴,Chen Siqiong¹²

Affiliation:

1. National Engineering Research Center for GIS Wuhan China

2. School of Geography and Information Engineering China University of Geosciences Wuhan China

3. College of Computer and Information Technology China Three Gorges University Yichang China

4. Wuhan Zondy Cyber Science & Technology Co. Ltd. Wuhan China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

American Geophysical Union (AGU)

Subject

General Earth and Planetary Sciences,Environmental Science (miscellaneous)

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1029/2021EA001673

Reference55 articles.

1. Research on segmentation of geological mineral text using conditional random field;Chen J.;China Mining Magazine,2018

2. Current situation and prospect of structure‐attribute integrated 3D geological modeling technology for geological big data;Chen Q.;Bulletin of Geological Science and Technology,2020

3. Gated Recursive Neural Network for Chinese Word Segmentation

4. Geological entity recognition based on ELMO‐CNN‐BiLSTM‐CRF Model;Chu D.;Earth science,2020

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