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The effectiveness of knowledge graph embedding (KGE) largely depends on the ability to model intrinsic relation patterns and mapping properties.
Unitary triangularization of a nonsymmetric matrix
Householder, A. S · 1958
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Wordnet: a lexical database for english
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Yago: a core of semantic knowledge
Suchanek, F. M., Kasneci, G., and Weikum, G · 2007
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Freebase: a collaboratively created graph database for structuring human knowledge
Bollacker, K., Evans, C., Paritosh, P., Sturge, T., and Taylor, J · 2008
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Learning structured embeddings of knowledge bases
Bordes, A., Weston, J., Collobert, R., and Bengio, Y · 2011
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Random search for hyper-parameter optimization
Bergstra, J. and Bengio, Y · 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
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Knowledge graph embedding by translating on hyperplanes
Wang, Z., Zhang, J., Feng, J., and Chen, Z · 2014
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Knowledge graph embedding via dynamic mapping matrix
Ji, G., He, S., Xu, L., Liu, K., and Zhao, J · 2015
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Adam: A method for stochastic optimization
Kingma, D. P. and Ba, J · 2015
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Learning entity and relation embeddings for knowledge graph completion
Lin, Y., Liu, Z., Sun, M., Liu, Y., and Zhu, X · 2015
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Yago3: A knowledge base from multilingual wikipedias
Mahdisoltani, F., Biega, J., and Suchanek, F · 2015
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Observed versus latent features for knowledge base and text inference
Toutanova, K. and Chen, D · 2015
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Transa: An adaptive approach for knowledge graph embedding
Xiao, H., Huang, M., Hao, Y., and Zhu, X · 2015
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Embedding entities and relations for learning and inference in knowledge bases
Yang, B., Yih, W., He, X., Gao, J., and Deng, L · 2015
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Explicit semantic ranking for academic search via knowledge graph embedding
Xiong, C., Power, R., and Callan, J · 2017
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Convolutional 2d knowledge graph embeddings
Dettmers, T., Minervini, P., Stenetorp, P., and Riedel, S · 2018
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A novel embedding model for knowledge base completion based on convolutional neural network
Nguyen, D. Q., Nguyen, T. D., Nguyen, D. Q., and Phung, D · 2018
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Modeling relational data with graph convolutional networks
Schlichtkrull, M., Kipf, T. N., Bloem, P., Van Den Berg, R., Titov, I., and Welling, M · 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
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Quaternion knowledge graph embeddings
Zhang, S., Tay, Y., Yao, L., and Liu, Q · 2019
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Geometric algebra
Artin, E · 2016
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Complex embeddings for simple link prediction
Trouillon, T., Welbl, J., Riedel, S., Gaussier, É., and Bouchard, G · 2016
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Knowledge base completion: Baselines strike back
Kadlec, R., Bajgar, O., and Kleindienst, J · 2017
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Rotate3d: Representing relations as rotations in three-dimensional space for knowledge graph embedding
Gao, C., Sun, C., Shan, L., Lin, L., and Wang, M · 2020
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Dual quaternion knowledge graph embeddings
Cao, Z., Xu, Q., Yang, Z., Cao, X., and Huang, Q · 2021
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Rot-pro: Modeling transitivity by projection in knowledge graph embedding
Song, T., Luo, J., and Huang, L · 2021
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