# Sudden Event Prediction Based on Event Knowledge Graph
## 4 Methods
### Event Knowledge Graph Construction--Taking the Traffic Domain as an Example
(2020) [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] A hybrid method of recurrent neural network and graph neural network for next-period prescription prediction. _Intl. J. Mach. Learn. Cybern._**2020**, _11_, 2849-2856. [CrossRef] [PubMed]
* [PERSON] et al. (2014) [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; et al. 'Beating the news' with EMBERS: Forecasting civil unrest using open source indicators. In Proceedings of the 20 th ACM SIGKDD International Conference on Knowledge Discovery and Data mining, New York, NY, USA, 24-27 August 2014; pp. 1799-1808. * [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Dynamic heterogeneous graph neural network for real-time event prediction. In Proceedings of the 26 th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, San Diego, CA, USA, 23-27 August 2020; pp. 3213-3223. * [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] RatGCN: Knowledge-Aware Attention Based Temporal Graph Convolutional Network for Multi-Event Prediction. In Proceedings of the 33 rd International Conference on Software Engineering & Knowledge Engineering, Pittsburgh, PA, USA, 1-10 July 2021. * [PERSON] et al. (2013) [PERSON]; [PERSON] [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON] Translating embeddings for modeling multi-relational data. _Adv. Neural Inf. Process. Syst._**2013**, _26_, 2787-2795. * [PERSON] et al. (2014) [PERSON]; [PERSON]; [PERSON]; [PERSON] Knowledge graph embedding by translating on hyperplanes. In Proceedings of the AAAI Conference on Artificial Intelligence, Quebec, QC, Canada, 27-31 July 2014; Volume 28. * [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Learning entity and relation embeddings for knowledge graph completion. In Proceedings of the AAAI Conference on Artificial Intelligence, Austin, TX, USA, 25-30 January 2015. * [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Knowledge graph embedding via dynamic mapping matrix. In Proceedings of the 53 rd Annual Meeting of the Association for Computational Linguistics and the 7 th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Beijing, China, 26-31 July 2015; pp. 687-696. * [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Event Relation Reasoning Based on Event Knowledge Graph. In Proceedings of the 14 th International Conference on Knowledge Science, Engineering and Management, Tokyo, Japan, 14-16 August 2021; pp. 491-503. * [PERSON] et al. (2020) [PERSON]; [PERSON]; [PERSON]; [PERSON] Heterogeneous graph transformer. In Proceedings of the 29 th International World Wide Web Conference, Taipei, China, 20-24 April 2020; pp. 2704-2710. * [PERSON] et al. (2014) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] [PERSON] Adverse drug event prediction combining shallow analysis and machine learning. In Proceedings of the 5 th International Workshop on Health Text Mining and Information Analysis (Louhi), Gothenburg, Sweden, 26-30 April 2014; pp. 85-89. * [PERSON] et al. (2005) [PERSON]; [PERSON]; [PERSON] Discovering frequent episodes and learning hidden markov models: A formal connection. _IEEE Trans. Knowl. Data Eng._**2005**, _17_, 1505-1517. [CrossRef]
* [PERSON] and [PERSON] (2008) [PERSON]; [PERSON]; [PERSON] Stream prediction using a generative model based on frequent episodes in event sequences. In Proceedings of the 14 th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Las Vegas, NE, USA, 24-27 August 2008; pp. 453-461. * [PERSON] et al. (2015) [PERSON]; [PERSON]; [PERSON] A pattern based predictor for event streams. _Expert Syst. Appl._**2015**, _42_, 9294-9306. [CrossRef]
* [PERSON] and [PERSON] (2012) [PERSON]; [PERSON] [PERSON] Customer event history for churn prediction: How long is long enough? _Expert Syst. Appl._**2012**, _39_, 13517-13522.