TANGO: A temporal spatial dynamic graph model for event prediction

Author:

Wang Zhihao,Ding Ding,Ren Min,Conti Mauro

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference47 articles.

1. A. Bordes, N. Usunier, A. Garcia-Duran, J. Weston, O. Yakhnenko, Translating embeddings for modeling multi-relational data, in: Advances in neural information processing systems, 2013, pp. 2787–2795.

2. Convolutional 2d knowledge graph embeddings;Dettmers,2018

3. Gdelt: Global data on events, location, and tone, 1979–2012;Leetaru,2013

4. E. Boschee, J. Lautenschlager, S. O’Brien, S. Shellman, J. Starz, M. Ward, Icews coded event data.

5. T. Jiang, T. Liu, T. Ge, L. Sha, B. Chang, S. Li, Z. Sui, Towards time-aware knowledge graph completion, in: Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, 2016, pp. 1715–1724.

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1. A task‐centric knowledge graph construction method based on multi‐modal representation learning for industrial maintenance automation;Engineering Reports;2024-07-07

2. Contrastive Hawkes graph neural networks with dynamic sampling for event prediction;Neurocomputing;2024-03

3. Confidence-based Modeling of Temporal Knowledge Graphs;Proceedings of the 2024 Guangdong-Hong Kong-Macao Greater Bay Area International Conference on Digital Economy and Artificial Intelligence;2024-01-19

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