Comprehending international important Ramsar wetland documents using latent semantic topic model in kernel space-Reference-Cited by-同舟云学术

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Comprehending international important Ramsar wetland documents using latent semantic topic model in kernel space

Published:2019-02-25 Issue:4 Volume:32 Page:
ISSN:0890-8575
Container-title:Natural Resource Modeling
language:en
Short-container-title:Natural Resource Modeling

Author:

Lin Ping¹²,Jiang Shanchao¹²,Li Du¹²,Zou Zhiyong³,Chen Yongming¹²^ORCID

Affiliation:

1. College of Electrical Engineering, Yancheng Institute of TechnologyYancheng Jiangsu China

2. Key Laboratory for Advanced Technology in Environmental Protection of Jiangsu Province, Yancheng Institute of TechnologyYancheng Jiangsu China

3. College of Mechanical and Electrical Engineering, Sichuan Agricultural UniversityYa'an Sichuan China

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Wiley

Subject

Environmental Science (miscellaneous),Modelling and Simulation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/nrm.12215

Reference45 articles.

1. 10.1162/jmlr.2003.3.4-5.993

2. A new method for perceiving origins of international important Ramsar wetland ecological habitat scenes in China

3. Search engine reinforced semi-supervised classification and graph-based summarization of microblogs

4. Support-vector networks

5. Warmer temperature accelerates methane emissions from the Zoige wetland on the Tibetan Plateau without changing methanogenic community composition

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