Information Propagation Prediction Based on Spatial–Temporal Attention and Heterogeneous Graph Convolutional Networks
Author:
Affiliation:
1. School of Computer Science and Engineering, Chongqing University of Technology, Chongqing, China
2. MIFT Department, University of Messina, Messina, Italy
3. Department of Computer Science, University of Messina, Messina, Italy
Funder
Science and Technology Research Project of Chongqing Municipal Education Commission
Graduate Innovation Fund of Chongqing University of Technology
2020 Chongqing Municipal Human Resources and Social Security Bureau of Innovation Project for Returned Overseas Person
2020 National Statistical Science Research Project
General Project of Chongqing Natural Science Foundation
2021 National Education Examination Research Project
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Human-Computer Interaction,Social Sciences (miscellaneous),Modeling and Simulation
Link
http://xplorestaging.ieee.org/ielx7/6570650/10414252/10064247.pdf?arnumber=10064247
Reference31 articles.
1. Online flu epidemiological deep modeling on disease contact network
2. DeepCas
3. Information Diffusion Prediction via Recurrent Cascades Convolution
4. Popularity Prediction on Social Platforms with Coupled Graph Neural Networks
5. Neural Diffusion Model for Microscopic Cascade Study
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