Open Access
Issue |
ITM Web Conf.
Volume 47, 2022
2022 2nd International Conference on Computer, Communication, Control, Automation and Robotics (CCCAR2022)
|
|
---|---|---|
Article Number | 02027 | |
Number of page(s) | 10 | |
Section | Algorithm Optimization and Application | |
DOI | https://doi.org/10.1051/itmconf/20224702027 | |
Published online | 23 June 2022 |
- Wangwang, Z., Peiyang, Yao., Jie, Z. 2018 Combat intention recognition for aerial targets based on deep neural network. Acta Areomauticaet Astronautica Sinical vol 39 p 195-203. [Google Scholar]
- Zhongyang, Li., Sendong, Z., Xiao, D.2017 EEG: Knowledge Base for Event Evolutionary Principles and Patterns. Chinese National Conference on Social Media Processing p 40-52. [Google Scholar]
- Ting L.2017 From Knowledge graph to event evolutionary graph 2017 China Computer Conference. https://blog.csdn.net/tgqdt3ggamdkhaslzv/article/details/78557548. [Google Scholar]
- ACE 2005 (Automatic Content Extraction) Chinese Annotation Guidelines for Events. [Google Scholar]
- Gang L., Shiyun W., Jin M.2021 Research on the construction of national security event graph for situation awareness. Journal of information vol 11 p 1164-1175. [Google Scholar]
- Xiao, D., Yue, Z., Ting, L. 2015 Deep learning for event-driven stock prediction. IJCAI, p 2327-2333 [Google Scholar]
- Pan, S., Qi, W., Huaiyu, W.2021 Script event prediction method combining event chain and event graph. Computer engineering vol 1 p 1-11 [Google Scholar]
- Wang, Z, Zhang, Y., Chang, Y. 2017 Integrating order information and event relation for script event prediction. Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing p 57-67 [Google Scholar]
- Li, Z., Ding, X., Liu, T.2019 Constructing narrative event evolutionary graph for script event prediction. IJCAI’18: Proceedings of the 27th International Joint Conference on Artificial Intelligence (AAAI Press) p 4201-4207 [Google Scholar]
- Jin, W., Zhang, C., Szekely, P. 2019 Recurrent event network for reasoning over temporal knowledge graphs. ICLR RLGM Workshop. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.