Fetching the paper…
Reading the bibliography…
Knowledge graph (KG) embedding encodes the entities and relations from a KG into low-dimensional vector spaces to support various applications such as KG completion, question answering, and recommender systems.
R. Caruana, S. Lawrence, C. L. Giles, Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping, in: NIPS, 2001, pp. 402–408
2001
Earlier work this paper cites.
R. Caruana, S. Lawrence, C. L. Giles, Overfitting in Neural Nets: Backpropagation, Conjugate Gradient, and Early Stopping, in: NIPS, 2001, pp. 402–408
2001
Earlier work this paper cites.
K. Bollacker, C. Evans, P. Paritosh, T. Sturge, J. Taylor, Freebase: A Collaboratively Created Graph Database for Structuring Human Knowledge, in: SIGMOD, 2008, pp. 1247–1250
2008
Earlier work this paper cites.
K. Bollacker, C. Evans, P. Paritosh, T. Sturge, J. Taylor, Freebase: A Collaboratively Created Graph Database for Structuring Human Knowledge, in: SIGMOD, 2008, pp. 1247–1250
2008
Earlier work this paper cites.
S. Hellmann, C. Stadler, J. Lehmann, S. Auer, DBpedia Live Extraction, in: OTM Conferences, 2009, pp. 1209–1223
2009
Earlier work this paper cites.
S. Hellmann, C. Stadler, J. Lehmann, S. Auer, DBpedia Live Extraction, in: OTM Conferences, 2009, pp. 1209–1223
2009
Earlier work this paper cites.
M. Nickel, V. Tresp, H.-P. Kriegel, A Three-Way Model for Collective Learning on Multi-Relational Data, in: ICML, Vol. 11, 2011, pp. 809–816
2011
Earlier work this paper cites.
S. S. Dasgupta, S. N. Ray, P. Talukdar, HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding, in: EMNLP, 2018, pp. 2001–2011
2011
Earlier work this paper cites.
M. Nickel, V. Tresp, H.-P. Kriegel, A Three-Way Model for Collective Learning on Multi-Relational Data, in: ICML, Vol. 11, 2011, pp. 809–816
2011
Earlier work this paper cites.
S. S. Dasgupta, S. N. Ray, P. Talukdar, HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding, in: EMNLP, 2018, pp. 2001–2011
2011
Earlier work this paper cites.
P. Wang, S. Li, R. Pan, Incorporating gan for negative sampling in knowledge representation learning, in: AAAI, 2018, pp. 2005–2012
2012
Earlier work this paper cites.
P. Wang, S. Li, R. Pan, Incorporating gan for negative sampling in knowledge representation learning, in: AAAI, 2018, pp. 2005–2012
2012
Earlier work this paper cites.
A. Bordes, N. Usunier, A. Garcia-Duran, J. Weston, O. Yakhnenko, Translating Embeddings for Modeling Multi-Relational Data, in: NIPS, 2013, pp. 2787–2795
2013
Earlier work this paper cites.
A. Khan, Y. Wu, C. C. Aggarwal, X. Yan, NeMa: Fast Graph Search with Label Similarity, PVLDB 6 (3) (2013) 181–192
2013
Earlier work this paper cites.
J. Bruna, W. Zaremba, A. Szlam, Y. LeCun, Spectral Networks and Locally Connected Networks on Graphs, in: ICLR, 2013
2013
Earlier work this paper cites.
A. Bordes, N. Usunier, A. Garcia-Duran, J. Weston, O. Yakhnenko, Translating Embeddings for Modeling Multi-Relational Data, in: NIPS, 2013, pp. 2787–2795
2013
Earlier work this paper cites.
A. Khan, Y. Wu, C. C. Aggarwal, X. Yan, NeMa: Fast Graph Search with Label Similarity, PVLDB 6 (3) (2013) 181–192
2013
Earlier work this paper cites.
J. Bruna, W. Zaremba, A. Szlam, Y. LeCun, Spectral Networks and Locally Connected Networks on Graphs, in: ICLR, 2013
2013
Earlier work this paper cites.
Z. Wang, J. Zhang, J. Feng, Z. Chen, Knowledge Graph Embedding by Translating on Hyperplanes, in: AAAI, Vol. 14, 2014, pp. 1112–1119
2014
Earlier work this paper cites.
Z. Wang, J. Zhang, J. Feng, Z. Chen, Knowledge Graph Embedding by Translating on Hyperplanes, in: AAAI, Vol. 14, 2014, pp. 1112–1119
2014
Earlier work this paper cites.
J. Lehmann, R. Isele, M. Jakob, A. Jentzsch, D. Kontokostas, P. N. Mendes, S. Hellmann, M. Morsey, P. Van Kleef, S. Auer, et al., DBpedia–a large-scale, multilingual knowledge base extracted from Wikipedia, Semantic Web 6 (2) (2015) 167–195
2015
Earlier work this paper cites.
F. Mahdisoltani, J. Biega, F. M. Suchanek, YAGO3: A Knowledge Base from Multilingual Wikipedias, in: CIDR, 2015
2015
Earlier work this paper cites.
B. Yang, W.-t. Yih, X. He, J. Gao, L. Deng, Embedding Entities and Relations for Learning and Inference in Knowledge Bases, in: ICLR, 2015
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
D. Bahdanau, K. Cho, Y. Bengio, Neural Machine Translation by Jointly Learning to Align and Translate, in: ICLR, 2015
2015
Earlier work this paper cites.
Y. Lin, Z. Liu, M. Sun, Y. Liu, X. Zhu, Learning Entity and Relation Embeddings for Knowledge Graph Completion, in: AAAI, Vol. 15, 2015, pp. 2181–2187
2015
Earlier work this paper cites.
G. Ji, S. He, L. Xu, K. Liu, J. Zhao, Knowledge Graph Embedding via Dynamic Mapping Matrix, in: ACL, Vol. 1, 2015, pp. 687–696
2015
Earlier work this paper cites.
J. Lehmann, R. Isele, M. Jakob, A. Jentzsch, D. Kontokostas, P. N. Mendes, S. Hellmann, M. Morsey, P. Van Kleef, S. Auer, et al., DBpedia–a large-scale, multilingual knowledge base extracted from Wikipedia, Semantic Web 6 (2) (2015) 167–195
2015
Earlier work this paper cites.
F. Mahdisoltani, J. Biega, F. M. Suchanek, YAGO3: A Knowledge Base from Multilingual Wikipedias, in: CIDR, 2015
2015
Earlier work this paper cites.
B. Yang, W.-t. Yih, X. He, J. Gao, L. Deng, Embedding Entities and Relations for Learning and Inference in Knowledge Bases, in: ICLR, 2015
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
D. Bahdanau, K. Cho, Y. Bengio, Neural Machine Translation by Jointly Learning to Align and Translate, in: ICLR, 2015
2015
Earlier work this paper cites.
Y. Lin, Z. Liu, M. Sun, Y. Liu, X. Zhu, Learning Entity and Relation Embeddings for Knowledge Graph Completion, in: AAAI, Vol. 15, 2015, pp. 2181–2187
2015
Earlier work this paper cites.
G. Ji, S. He, L. Xu, K. Liu, J. Zhao, Knowledge Graph Embedding via Dynamic Mapping Matrix, in: ACL, Vol. 1, 2015, pp. 687–696
2015
Earlier work this paper cites.
J. Feng, M. Huang, Y. Yang, et al., GAKE: Graph Aware Knowledge Embedding, in: COLING, 2016, pp. 641–651
2016
Earlier work this paper cites.
T. Jiang, T. Liu, T. Ge, L. Sha, B. Chang, S. Li, Z. Sui, Towards Time-Aware Knowledge Graph Completion, in: COLING, 2016, pp. 1715–1724
2016
Earlier work this paper cites.
M. Defferrard, X. Bresson, P. Vandergheynst, Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering, in: NIPS, 2016, pp. 3844–3852
2016
Earlier work this paper cites.
G. Ji, K. Liu, S. He, J. Zhao, Knowledge Graph Completion with Adaptive Sparse Transfer Matrix, in: AAAI, 2016, pp. 985–991
2016
Earlier work this paper cites.
J. Feng, M. Huang, Y. Yang, et al., GAKE: Graph Aware Knowledge Embedding, in: COLING, 2016, pp. 641–651
2016
Cited alongside, same era.
T. Jiang, T. Liu, T. Ge, L. Sha, B. Chang, S. Li, Z. Sui, Towards Time-Aware Knowledge Graph Completion, in: COLING, 2016, pp. 1715–1724
2016
Cited alongside, same era.
M. Defferrard, X. Bresson, P. Vandergheynst, Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering, in: NIPS, 2016, pp. 3844–3852
2016
Cited alongside, same era.
G. Ji, K. Liu, S. He, J. Zhao, Knowledge Graph Completion with Adaptive Sparse Transfer Matrix, in: AAAI, 2016, pp. 985–991
2016
Cited alongside, same era.
Q. Wang, Z. Mao, B. Wang, L. Guo, Knowledge Graph Embedding: A Survey of Approaches and Applications, IEEE Transactions on Knowledge and Data Engineering 29 (12) (2017) 2724–2743
2017
X. Han, S. Cao, X. Lv, Y. Lin, Z. Liu, M. Sun, J. Li, OpenKE: An Open Toolkit for Knowledge Embedding, in: EMNLP, 2018, pp. 139–144
2018
Later among the works it cites.
W. Zheng, J. X. Yu, L. Zou, H. Cheng, Question Answering over Knowledge Graphs: Question Understanding via Template Decomposition, PVLDB 11 (11) (2018) 1373–1386
2018
Later among the works it cites.
Y. Jia, Y. Wang, X. Jin, H. Lin, X. Cheng, Knowledge Graph Embedding: A Locally and Temporally Adaptive Translation-Based Approach, ACM Transactions on the Web 12 (2) (2018) 8
2018
Later among the works it cites.
L. Zhou, Y. Yang, X. Ren, F. Wu, Y. Zhuang, Dynamic Network Embedding by Modeling Triadic Closure Process, in: AAAI, 2018
2018
Later among the works it cites.
Z. Sun, Z.-H. Deng, J.-Y. Nie, J. Tang, RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space, in: ICLR, 2019
2019
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
W. Hamilton, Z. Ying, J. Leskovec, Inductive Representation Learning on Large Graphs, in: NIPS, 2017, pp. 1024–1034
2017
Cited alongside, same era.
J. Li, H. Dani, X. Hu, J. Tang, Y. Chang, H. Liu, Attributed Network Embedding for Learning in a Dynamic Environment, in: CIKM, 2017, pp. 387–396
2017
Cited alongside, same era.
R. Trivedi, H. Dai, Y. Wang, L. Song, Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs, in: ICML, 2017, pp. 3462–3471
2017
Cited alongside, same era.
Y. Tay, A. T. Luu, S. C. Hui, Non-Parametric Estimation of Multiple Embeddings for Link Prediction on Dynamic Knowledge Graphs, in: AAAI, 2017, pp. 1243–1249
2017
Cited alongside, same era.
J. Xu, X. Qiu, K. Chen, X. Huang, Knowledge Graph Representation with Jointly Structural and Textual Encoding, in: IJCAI, 2017, pp. 1318–1324
2017
Cited alongside, same era.
J. Jin, J. Luo, S. Khemmarat, L. Gao, Querying Web-Scale Knowledge Graphs Through Effective Pruning of Search Space, IEEE Transactions on Parallel and Distributed Systems 28 (8) (2017) 2342–2356
2017
Cited alongside, same era.
T. N. Kipf, M. Welling, Semi-Supervised Classification with Graph Convolutional Networks, ICLR (2017)
2017
Cited alongside, same era.
Closest in time.
R. Trivedi, M. Farajtabar, P. Biswal, H. Zha, DyRep: Learning Representations over Dynamic Graphs, in: ICLR, 2019
2019
Closest in time.
Y. Zhang, Q. Yao, Y. Shao, L. Chen, NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding, in: ICDE, 2019, pp. 614–625
2019
Closest in time.
X. Huang, J. Zhang, D. Li, P. Li, Knowledge Graph Embedding Based Question Answering, in: WSDM, 2019, pp. 105–113
2019
Closest in time.
Z. Sun, Z.-H. Deng, J.-Y. Nie, J. Tang, RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space, in: ICLR, 2019
2019
Closest in time.
R. Trivedi, M. Farajtabar, P. Biswal, H. Zha, DyRep: Learning Representations over Dynamic Graphs, in: ICLR, 2019
2019
Closest in time.
Y. Zhang, Q. Yao, Y. Shao, L. Chen, NSCaching: Simple and Efficient Negative Sampling for Knowledge Graph Embedding, in: ICDE, 2019, pp. 614–625
2019
Closest in time.
X. Huang, J. Zhang, D. Li, P. Li, Knowledge Graph Embedding Based Question Answering, in: WSDM, 2019, pp. 105–113
2019
Closest in time.
Z. Liu, C. Huang, Y. Yu, P. Song, B. Fan, J. Dong, Dynamic Representation Learning for Large-Scale Attributed Networks, in: CIKM, 2020, pp. 1005–1014
2020
Closest in time.
R. Goel, S. M. Kazemi, M. Brubaker, P. Poupart, Diachronic Embedding for Temporal Knowledge Graph Completion, in: AAAI, Vol. 34, 2020, pp. 3988–3995
2020
Closest in time.
W. Jin, M. Qu, X. Jin, X. Ren, Recurrent Event Network: Autoregressive Structure Inferenceover Temporal Knowledge Graphs, in: EMNLP, 2020, pp. 6669–6683
2020
Closest in time.
2020
Closest in time.
Z. Liu, C. Huang, Y. Yu, P. Song, B. Fan, J. Dong, Dynamic Representation Learning for Large-Scale Attributed Networks, in: CIKM, 2020, pp. 1005–1014
2020
Closest in time.
R. Goel, S. M. Kazemi, M. Brubaker, P. Poupart, Diachronic Embedding for Temporal Knowledge Graph Completion, in: AAAI, Vol. 34, 2020, pp. 3988–3995
2020
Closest in time.
W. Jin, M. Qu, X. Jin, X. Ren, Recurrent Event Network: Autoregressive Structure Inferenceover Temporal Knowledge Graphs, in: EMNLP, 2020, pp. 6669–6683
2020
Closest in time.
2020
Closest in time.
Z. Liu, C. Huang, Y. Yu, J. Dong, Motif-Preserving Dynamic Attributed Network Embedding, in: The Web Conference, 2021, pp. 1629–1638
2021
Closest in time.
C. D. Barros, M. R. Mendonça, A. B. Vieira, A. Ziviani, A Survey on Embedding Dynamic Graphs, ACM Computing Surveys (CSUR) 55 (1) (2021) 1–37
2021
Closest in time.
Z. Li, X. Jin, W. Li, S. Guan, J. Guo, H. Shen, Y. Wang, X. Cheng, Temporal Knowledge Graph Reasoning based on Evolutional Representation Learning, in: SIGIR, 2021, pp. 408–417
2021
Closest in time.
L. Fei, T. Wu, A. Khan, Online Updates of Knowledge Graph Embedding, in: COMPLEX NETWORKS, 2021, pp. 523–535
2021
Closest in time.
A. Daruna, M. Gupta, M. Sridharan, S. Chernova, Continual Learning of Knowledge Graph Embeddings, IEEE Robotics and Automation Letters 6 (2) (2021) 1128–1135
2021
Closest in time.
Z. Liu, C. Huang, Y. Yu, J. Dong, Motif-Preserving Dynamic Attributed Network Embedding, in: The Web Conference, 2021, pp. 1629–1638
2021
Closest in time.
C. D. Barros, M. R. Mendonça, A. B. Vieira, A. Ziviani, A Survey on Embedding Dynamic Graphs, ACM Computing Surveys (CSUR) 55 (1) (2021) 1–37
2021
Closest in time.
Z. Li, X. Jin, W. Li, S. Guan, J. Guo, H. Shen, Y. Wang, X. Cheng, Temporal Knowledge Graph Reasoning based on Evolutional Representation Learning, in: SIGIR, 2021, pp. 408–417
2021
Closest in time.
L. Fei, T. Wu, A. Khan, Online Updates of Knowledge Graph Embedding, in: COMPLEX NETWORKS, 2021, pp. 523–535
2021
Closest in time.
A. Daruna, M. Gupta, M. Sridharan, S. Chernova, Continual Learning of Knowledge Graph Embeddings, IEEE Robotics and Automation Letters 6 (2) (2021) 1128–1135
2021
Closest in time.
2022
Closest in time.
2022
Closest in time.
2022
Closest in time.
2022
Closest in time.
T. Trouillon, J. Welbl, S. Riedel, É. Gaussier, G. Bouchard, Complex Embeddings for Simple Link Prediction, in: ICML, 2016, pp. 2071–2080
2080
Closest in time.
T. Trouillon, J. Welbl, S. Riedel, É. Gaussier, G. Bouchard, Complex Embeddings for Simple Link Prediction, in: ICML, 2016, pp. 2071–2080
2080
Closest in time.
L. Du, Y. Wang, G. Song, Z. Lu, J. Wang, Dynamic Network Embedding: An Extended Approach for Skip-gram based Network Embedding, in: IJCAI, 2018, pp. 2086–2092
2092
Closest in time.
L. Du, Y. Wang, G. Song, Z. Lu, J. Wang, Dynamic Network Embedding: An Extended Approach for Skip-gram based Network Embedding, in: IJCAI, 2018, pp. 2086–2092
2092
Closest in time.