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Large knowledge graphs often grow to store temporal facts that model the dynamic relations or interactions of entities along the timeline.
Recurrent Event Network: Global Structure Inference over Temporal Knowledge Graph
Jin, W.; Jiang, H.; Qu, M.; Chen, T.; Zhang, C.; Szekely, P.; and Ren, X. 2019 · 1904
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A survey on knowledge graphs: Representation, acquisition and applications
Ji, S.; Pan, S.; Cambria, E.; Marttinen, P.; and Yu, P. S. 2020 · 2002
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Diplomatic handbook
Feltham, R. 2004 · 2004
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Simulating the East African wildebeest migration patterns using GIS and remote sensing
Musiega, D. E.; and Kazadi, S.-N. 2004 · 2004
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Matrix factorization techniques for recommender systems
Koren, Y.; Bell, R.; and Volinsky, C. 2009 · 2009
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A spectral analysis of world GDP dynamics: Kondratieff waves, Kuznets swings, Juglar and Kitchin cycles in global economic development, and the 2008–2009 economic crisis
Korotayev, A. V.; and Tsirel, S. V. 2010 · 2009
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Understanding the difficulty of training deep feedforward neural networks
Glorot, X.; and Bengio, Y. 2010 · 2010
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System and method for generating transaction based recommendations
Lortscher Jr, F. D. 2010 · 2010
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Hyte: Hyperplane-based temporally aware knowledge graph embedding
Dasgupta, S. S.; Ray, S. N.; and Talukdar, P. 2018 · 2011
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Temporal events analysis employing tree induction
Bouchard, G.; and Andreoli, J.-M. 2012 · 2012
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Translating embeddings for modeling multi-relational data
Bordes, A.; Usunier, N.; Garcia-Duran, A.; Weston, J.; and Yakhnenko, O. 2013 · 2013
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GDELT: Global data on events, location, and tone
Leetaru, K.; and Schrodt, P. A. 2013 · 2013
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Yago3: A knowledge base from multilingual wikipedias
Mahdisoltani, F.; Biega, J.; and Suchanek, F. M. 2013 · 2013
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Knowledge graph embedding by translating on hyperplanes
Wang, Z.; Zhang, J.; Feng, J.; and Chen, Z. 2014 · 2014
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ICEWS coded event data
Boschee, E.; Lautenschlager, J.; O’Brien, S.; Shellman, S.; Starz, J.; and Ward, M. 2015 · 2015
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Knowledge graph embedding via dynamic mapping matrix
Ji, G.; He, S.; Xu, L.; Liu, K.; and Zhao, J. 2015 · 2015
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Pointer networks
Vinyals, O.; Fortunato, M.; and Jaitly, N. 2015 · 2015
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Embedding entities and relations for learning and inference in knowledge bases
Yang, B.; Yih, W.-t.; He, X.; Gao, J.; and Deng, L. 2015 · 2015
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Recurrent marked temporal point processes: Embedding event history to vector
Du, N.; Dai, H.; Trivedi, R.; Upadhyay, U.; Gomez-Rodriguez, M.; and Song, L. 2016 · 2016
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Incorporating Copying Mechanism in Sequence-to-Sequence Learning
Gu, J.; Lu, Z.; Li, H.; and Li, V. O. 2016 · 2016
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Towards time-aware knowledge graph completion
Jiang, T.; Liu, T.; Ge, T.; Sha, L.; Chang, B.; Li, S.; and Sui, Z. 2016 · 2016
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Learning symmetric collaborative dialogue agents with dynamic knowledge graph embeddings
He, H.; Balakrishnan, A.; Eric, M.; and Liang, P. 2017 · 2017
Dyrep: Learning representations over dynamic graphs
Trivedi, R.; Farajtabar, M.; Biswal, P.; and Zha, H. 2018 · 2018
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TuckER: Tensor Factorization for Knowledge Graph Completion
Balazevic, I.; Allen, C.; and Hospedales, T. 2019 · 2019
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Incorporating structured commonsense knowledge in story completion
Chen, J.; Chen, J.; and Yu, Z. 2019 · 2019
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Learning to identify high betweenness centrality nodes from scratch: A novel graph neural network approach
Fan, C.; Zeng, L.; Ding, Y.; Chen, M.; Sun, Y.; and Liu, Z. 2019 · 2019
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Tensor Decompositions for Temporal Knowledge Base Completion
Lacroix, T.; Obozinski, G.; and Usunier, N. 2019 · 2019
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Embedding models for episodic knowledge graphs
Ma, Y.; Tresp, V.; and Daxberger, E. A. 2019 · 2019
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Semi-Supervised Classification with Graph Convolutional Networks
Kipf, T. N.; and Welling, M. 2017 · 2017
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Know-evolve: deep temporal reasoning for dynamic knowledge graphs
Trivedi, R.; Dai, H.; Wang, Y.; and Song, L. 2017 · 2017
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Knowledge graph embedding: A survey of approaches and applications
Wang, Q.; Mao, Z.; Wang, B.; and Guo, L. 2017 · 2017
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Convolutional 2D knowledge graph embeddings
Dettmers, T.; Minervini, P.; Stenetorp, P.; and Riedel, S. 2018 · 2018
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Learning Sequence Encoders for Temporal Knowledge Graph Completion
García-Durán, A.; Dumancic, S.; and Niepert, M. 2018 · 2018
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Simple embedding for link prediction in knowledge graphs
Kazemi, S. M.; and Poole, D. 2018 · 2018
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RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space
Sun, Z.; Deng, Z.-H.; Nie, J.-Y.; and Tang, J. 2019 · 2019
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Hybrid-TE: Hybrid Translation-Based Temporal Knowledge Graph Embedding
Wang, Z.; and Li, X. 2019 · 2019
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“What Are You Trying To Do?” Semantic Typing of Event Processes
Chen, M.; Zhang, H.; Wang, H.; and Roth, D. 2020 · 2020
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A Survey on Knowledge Graph Embedding: Approaches, Applications and Benchmarks
Dai, Y.; Wang, S.; Xiong, N. N.; and Guo, W. 2020 · 2020
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Diachronic embedding for temporal knowledge graph completion
Goel, R.; Kazemi, S. M.; Brubaker, M.; and Poupart, P. 2020 · 2020
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Bio-joie: Joint representation learning of biological knowledge bases
Hao, J.; Ju, C. J.-T.; Chen, M.; Sun, Y.; Zaniolo, C.; and Wang, W. 2020 · 2020
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Analogous Process Structure Induction for Sub-event Sequence Prediction
Zhang, H.; Chen, M.; Wang, H.; Song, Y.; and Roth, D. 2020 · 2020
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Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks
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Complex Embeddings for Simple Link Prediction
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