A cold-start recommendation method for We-map considering co-occurrence collaborative signals and contrastive learning-Reference-Cited by-同舟云学术

A cold-start recommendation method for We-map considering co-occurrence collaborative signals and contrastive learning

Published:2024-03-15 Issue: Volume: Page:1-20
ISSN:1449-8596
Container-title:Journal of Spatial Science
language:en
Short-container-title:Journal of Spatial Science

Author:

Ma Wenjun¹²³⁴^ORCID,Yan Haowen¹²³^ORCID,Li Jingzhong¹²³^ORCID,Wang Xiaolong⁵⁶^ORCID,Wang Zhuo⁷^ORCID,Yang Qili¹²³^ORCID,Fu Xuan¹²³^ORCID

Affiliation:

1. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou, China

2. National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou Jiaotong University, Lanzhou, China

3. Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou Jiaotong University, Lanzhou, China

4. Academician Expert Workstation of Gansu Dayu Jiuzhou Space Information Technology Co., Ltd., Lanzhou, China

5. College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China

6. Key Laboratory of Western China’s Environmental Systems, Ministry of Education, Lanzhou, China

7. School of Resources and Environmental Sciences, Wuhan University, Wuhan, China

Funder

The National Natural Science Foundation of China

The Graduate Education Teaching Quality Improvement Project of Lanzhou Jiaotong University

National Natural Science Foundation Major Program of China

The Open Fund of Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources

The Open Research Fund of Key Laboratory of Digital Earth Science, Chinese Academy of Sciences

The Natural Science Foundation of Hubei Province

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/14498596.2024.2325344

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