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Most real-world knowledge graphs (KG) are far from complete and comprehensive.
Partially supervised classification of text documents
B. Liu, W. Lee, P. Yu, and X. Li · 2002
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Bpr: Bayesian personalized ranking from implicit feedback
S. Rendle, C. Freudenthaler, Z. Gantner, and L. Schmidt-Thieme · 2009
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Translating embeddings for modeling multi-relational data
A. Bordes, N. Usunier, A. Garcia-Duran, J. Weston, and O. Yakhnenko · 2013
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Analysis of learning from positive and unlabeled data
M. Du Plessis, G. Niu, and M. Sugiyama · 2014
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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Embedding entities and relations for learning and inference in knowledge bases
B. Yang, W. Yih, X. He, J. Gao, and L. Deng · 2014
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Convex formulation for learning from positive and unlabeled data
M. Du Plessis, G. Niu, and M. Sugiyama · 2015
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Adam: A method for stochastic optimization
D. Kingma and J. Ba · 2015
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Type-constrained representation learning in knowledge graphs
D. Krompaß, S. Baier, and V. Tresp · 2015
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Representing text for joint embedding of text and knowledge bases
K. Toutanova, D. Chen, P. Pantel, H. Poon, P. Choudhury, and M. Gamon · 2015
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Class-prior estimation for learning from positive and unlabeled data
M. Christoffel, G. Niu, and M. Sugiyama · 2016
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Pairwise versus pointwise ranking: A case study
V. Melnikov, P. Gupta, B. Frick, D. Kaimann, and E. Hüllermeier · 2016
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Positive-unlabeled learning with non-negative risk estimator
R. Kiryo, G. Niu, M. du Plessis, and M. Sugiyama · 2017
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Sparsity and noise: Where knowledge graph embeddings fall short
J. Pujara, E. Augustine, and L. Getoor · 2017
Cited alongside, same era.
Knowledge graph completion via complex tensor factorization
T. Trouillon, C. Dance, É. Gaussier, J. Welbl, S. Riedel, and G. Bouchard · 2017
Cited alongside, same era.
Irgan: A minimax game for unifying generative and discriminative information retrieval models
J. Wang, L. Yu, W. Zhang, Y. Gong, Y. Xu, B. Wang, P. Zhang, and D. Zhang · 2017
Cited alongside, same era.
Kbgan: Adversarial learning for knowledge graph embeddings
L. Cai and William Y. Wang · 2018
Cited alongside, same era.
Convolutional 2d knowledge graph embeddings
T. Dettmers, P. Minervini, P. Stenetorp, and S. Riedel · 2018
Cited alongside, same era.
Instance-dependent pu learning by bayesian optimal relabeling
Positive-unlabeled reward learning
D. Xu and M. Denil · 2019
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Interaction embeddings for prediction and explanation in knowledge graphs
W. Zhang, B. Paudel, W. Zhang, A. Bernstein, and H. Chen · 2019
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Nscaching: simple and efficient negative sampling for knowledge graph embedding
Y. Zhang, Q. Yao, Y. Shao, and L. Chen · 2019
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Structure aware negative sampling in knowledge graphs
K. Ahrabian, A. Feizi, Y. Salehi, W. Hamilton, and Avishek J. Bose · 2020
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Temporal positive-unlabeled learning for biomedical hypothesis generation via risk estimation
U. Akujuobi, J. Chen, M. Elhoseiny, M. Spranger, and X. Zhang · 2020
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F. He, T. Liu, G. Webb, and D. Tao · 2018
Cited alongside, same era.
Simple embedding for link prediction in knowledge graphs
S. Kazemi and D. Poole · 2018
Cited alongside, same era.
Bagan: Data augmentation with balancing gan
G. Mariani, F. Scheidegger, R. Istrate, C. Bekas, and C. Malossi · 2018
Cited alongside, same era.
A novel embedding model for knowledge base completion based on convolutional neural network
T. Nguyen, D. Nguyen, D. Phung, et al · 2018
Cited alongside, same era.
Positive and unlabeled learning via loss decomposition and centroid estimation
H. Shi, S. Pan, J. Yang, and C. Gong · 2018
Cited alongside, same era.
Rotate: Knowledge graph embedding by relational rotation in complex space
Z. Sun, Z. Deng, J. Nie, and J. Tang · 2018
Cited alongside, same era.
Incorporating gan for negative sampling in knowledge representation learning
P. Wang, S. Li, and R. Pan · 2018
Cited alongside, same era.
J. Bekker and J. Davis · 2020
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Openbiolink: a benchmarking framework for large-scale biomedical link prediction
A. Breit, S. Ott, A. Agibetov, and M. Samwald · 2020
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A deep look into neural ranking models for information retrieval
J. Guo, Y. Fan, L. Pang, L. Yang, Q. Ai, H. Zamani, C. Wu, W. Croft, and X. Cheng · 2020
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Composition-based multi-relational graph convolutional networks
V. Shikhar, S. Soumya, N. Vikram, and T. Partha · 2020
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Relational graph neural network with hierarchical attention for knowledge graph completion
Z. Zhang, F. Zhuang, H. Zhu, Z. Shi, H. Xiong, and Q. He · 2020
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Learning knowledge graph embedding with heterogeneous relation attention networks
Z. Li, H. Liu, Z. Zhang, T. Liu, and N. Xiong · 2021
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Knowledge graph embedding for link prediction: A comparative analysis
A. Rossi, D. Barbosa, D. Firmani, A. Matinata, and P. Merialdo · 2021
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