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Embedding based Knowledge Graph (KG) Completion has gained much attention over the past few years.
1907
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W. Xiong, M. Yu, S. Chang, X. Guo and W.Y. Wang, One-Shot Relational Learning for Knowledge Graphs, in: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31 - November 4, 2018
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H. Paulheim and C. Bizer, Type Inference on Noisy RDF Data, in: ISWC
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Z. Wang, J. Zhang, J. Feng and Z. Chen, Knowledge Graph Embedding by Translating on Hyperplanes, in: Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence, July 27 -31, 2014, Québec City, Québec, Canada
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Y. Lin, Z. Liu, H. Luan, M. Sun, S. Rao and S. Liu, Modeling Relation Paths for Representation Learning of Knowledge Bases, in: Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP 2015, Lisbon, Portugal, September 17-21, 2015
2015
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K. Toutanova and D. Chen, Observed versus latent features for knowledge base and text inference, in: Proceedings of the 3rd Workshop on Continuous Vector Space Models and their Compositionality
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J. Feng, M. Huang, Y. Yang and X. Zhu, GAKE: Graph Aware Knowledge Embedding, in: COLING 2016, 26th International Conference on Computational Linguistics, Proceedings of the Conference: Technical Papers, December 11-16, 2016, Osaka, Japan
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P. Ristoski and H. Paulheim, RDF2Vec: RDF Graph Embeddings for Data Mining, in: The Semantic Web - ISWC 2016 - 15th International Semantic Web Conference, Kobe, Japan, October 17-21, 2016, Proceedings, Part I
2016
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R. Xie, Z. Liu and M. Sun, Representation Learning of Knowledge Graphs with Hierarchical Types, in: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI
2016
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A. Melo, H. Paulheim and J. Völker, Type Prediction in RDF Knowledge Bases Using Hierarchical Multilabel Classification, in: WIMS
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B. Xu, Y. Zhang, J. Liang, Y. Xiao, S. Hwang and W. Wang, Cross-Lingual Type Inference, in: International Conference Database Systems for Advanced Applications, DASFAA
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R. Xie, Z. Liu and M. Sun, Representation Learning of Knowledge Graphs with Hierarchical Types, in: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, IJCAI 2016, New York, NY, USA, 9-15 July 2016
2016
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R. Xie, Z. Liu, J. Jia, H. Luan and M. Sun, Representation Learning of Knowledge Graphs with Entity Descriptions, Proceedings of the AAAI Conference on Artificial Intelligence
2016
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H. Paulheim, Knowledge graph refinement: A survey of approaches and evaluation methods, Semantic Web
2017
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Q. Wang, Z. Mao, B. Wang and L. Guo, Knowledge Graph Embedding: A Survey of Approaches and Applications, IEEE Trans. Knowl. Data Eng
2017
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J. Xu, X. Qiu, K. Chen and X. Huang, Knowledge Graph Representation with Jointly Structural and Textual Encoding, in: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, Melbourne, Australia, August 19-25, 2017
2017
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F. Yang, Z. Yang and W.W. Cohen, Differentiable Learning of Logical Rules for Knowledge Base Reasoning, in: Proceedings of the 31st International Conference on Neural Information Processing Systems
2017
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W.L. Hamilton, R. Ying and J. Leskovec, Inductive Representation Learning on Large Graphs, in: Proceedings of the 31st International Conference on Neural Information Processing Systems
2017
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T. Hamaguchi, H. Oiwa, M. Shimbo and Y. Matsumoto, Knowledge Transfer for Out-of-Knowledge-Base Entities : A Graph Neural Network Approach, in: Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI-17
2017
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Y. Yaghoobzadeh and H. Schütze, Multi-level Representations for Fine-Grained Typing of Knowledge Base Entities, in: Conference of the European Chapter of the Association for Computational Linguistics
2017
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S. Ma, J. Ding, W. Jia, K. Wang and M. Guo, TransT: Type-Based Multiple Embedding Representations for Knowledge Graph Completion, in: Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2017, Skopje, Macedonia, September 18-22, 2017, Proceedings, Part I
2017
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M. Kulmanov and R. Hoehndorf, Evaluating the effect of annotation size on measures of semantic similarity, J. Biomed. Semant
2017
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C. Moon, P. Jones and N.F. Samatova, Learning Entity Type Embeddings for Knowledge Graph Completion, in: Proceedings of the 2017 ACM on Conference on Information and Knowledge Management
2017
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D. Szklarczyk, J.H. Morris, H. Cook, M. Kuhn, S. Wyder, M. Simonovic, A. Santos, N.T. Doncheva, A. Roth, P. Bork, L.J. Jensen and C. von Mering, The STRING database in 2017: quality-controlled protein-protein association networks, made broadly accessible, Nucleic Acids Res
2017
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T. Dettmers, P. Minervini, P. Stenetorp and S. Riedel, Convolutional 2D Knowledge Graph Embeddings, in: Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18)
2018
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M.S. Schlichtkrull, T.N. Kipf, P. Bloem, R. van den Berg, I. Titov and M. Welling, Modeling Relational Data with Graph Convolutional Networks, in: The Semantic Web - 15th International Conference, ESWC, Proceedings
2018
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C. Meilicke, M. Fink, Y. Wang, D. Ruffinelli, R. Gemulla and H. Stuckenschmidt, Fine-Grained Evaluation of Rule- and Embedding-Based Systems for Knowledge Graph Completion, in: SEMWEB
2018
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Y. Yaghoobzadeh, H. Adel and H. Schütze, Corpus-Level Fine-Grained Entity Typing, J. Artif. Intell. Res
2018
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H. Jin, L. Hou, J. Li and T. Dong, Attributed and Predictive Entity Embedding for Fine-Grained Entity Typing in Knowledge Bases, in: International Conference on Computational Linguistics
2018
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D.M. Dooley, E.J. Griffiths, G.P.S. Gosal, P.L. Buttigieg, R. Hoehndorf, M. Lange, L.M. Schriml, F.S.L. Brinkman and W.W.L. Hsiao, FoodOn: a harmonized food ontology to increase global food traceability, quality control and data integration, NPJ Science of Food
2018
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J. Chen, P. Hu, E. Jiménez-Ruiz, O.M. Holter, D. Antonyrajah and I. Horrocks, OWL2Vec*: embedding of OWL ontologies, Mach. Learn
2021
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S. Mondal, S. Bhatia and R. Mutharaju, EmEL++: Embeddings for EL++ Description Logic, in: Proceedings of the AAAI 2021 Spring Symposium on Combining Machine Learning and Knowledge Engineering (AAAI-MAKE 2021), Stanford University, Palo Alto, California, USA, March 22-24, 2021
2021
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C. d’Amato, N.F. Quatraro and N. Fanizzi, Injecting Background Knowledge into Embedding Models for Predictive Tasks on Knowledge Graphs, in: The Semantic Web
2021
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Y. Geng, J. Chen, Z. Chen, J.Z. Pan, Z. Ye, Z. Yuan, Y. Jia and H. Chen, OntoZSL: Ontology-enhanced Zero-shot Learning, in: WWW ’21: The Web Conference 2021, Virtual Event / Ljubljana, Slovenia, April 19-23, 2021
2021
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T. Dettmers, P. Minervini, P. Stenetorp and S. Riedel, Convolutional 2d knowledge graph embeddings, in: Thirty-Second AAAI Conference on Artificial Intelligence
2018
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M. Dragoni, T. Bailoni, R. Maimone and C. Eccher, HeLiS: An Ontology for Supporting Healthy Lifestyles, in: The Semantic Web - ISWC 2018 - 17th International Semantic Web Conference, Monterey, CA, USA, October 8-12, 2018, Proceedings, Part II
2018
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Z. Sun, Z. Deng, J. Nie and J. Tang, RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space, in: 7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019
2019
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C. Meilicke, M.W. Chekol, D. Ruffinelli and H. Stuckenschmidt, Anytime Bottom-Up Rule Learning for Knowledge Graph Completion, in: Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019
2019
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A. Sadeghian, M. Armandpour, P. Ding and D.Z. Wang, DRUM: End-to-End Differentiable Rule Mining on Knowledge Graphs
2019
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P. Wang, J. Han, C. Li and R. Pan, Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding, in: Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence and Thirty-First Innovative Applications of Artificial Intelligence Conference and Ninth AAAI Symposium on Educational Advances in Artificial Intelligence
2019
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H. Jin, L. Hou, J. Li and T. Dong, Fine-Grained Entity Typing via Hierarchical Multi Graph Convolutional Networks, in: Empirical Methods in Natural Language Processing and International Joint Conference on Natural Language Processing
2019
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J. Devlin, M. Chang, K. Lee and K. Toutanova, BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding, in: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
2019
Cited alongside, same era.
G.A. Gesese, M. Alam and H. Sack, LiterallyWikidata - A Benchmark for Knowledge Graph Completion using Literals, in: ISWC
2021
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G.A. Gesese, M. Alam and H. Sack, LiterallyWikidata - A Benchmark for Knowledge Graph Completion Using Literals, in: The Semantic Web - ISWC 2021 - 20th International Semantic Web Conference, ISWC 2021, Virtual Event, October 24-28, 2021, Proceedings
2021
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R. Biswas, H. Sack and M. Alam, MADLINK: Attentive Multihop and Entity Descriptions for Link Prediction in Knowledge Graphs, Semantic Web Journal
2022
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G.A. Gesese, H. Sack and M. Alam, RAILD: Towards Leveraging Relation Features for Inductive Link Prediction In Knowledge Graphs, in: Proceedings of the 11th International Joint Conference on Knowledge Graphs, IJCKG 2022, Hangzhou, China, October 27-28, 2022
2022
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R. Biswas, J. Portisch, H. Paulheim, H. Sack and M. Alam, Entity Type Prediction Leveraging Graph Walks and Entity Descriptions, in: International Semantic Web Conference (ISWC)
2022
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J. Zhuo, Q. Zhu, Y. Yue, Y. Zhao and W. Han, A Neighborhood-Attention Fine-grained Entity Typing for Knowledge Graph Completion, in: ACM International Conference on Web Search and Data Mining
2022
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X. Lv, Y. Lin, Y. Cao, L. Hou, J. Li, Z. Liu, P. Li and J. Zhou, Do Pre-trained Models Benefit Knowledge Graph Completion? A Reliable Evaluation and a Reasonable Approach, in: Findings of the Association for Computational Linguistics: ACL 2022, Dublin, Ireland, May 22-27, 2022
2022
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X. Xie, N. Zhang, Z. Li, S. Deng, H. Chen, F. Xiong, M. Chen and H. Chen, From Discrimination to Generation: Knowledge Graph Completion with Generative Transformer, in: Companion of The Web Conference
2022
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C. Chen, Y. Wang, B. Li and K. Lam, Knowledge Is Flat: A Seq2Seq Generative Framework for Various Knowledge Graph Completion, in: Proceedings of the 29th International Conference on Computational Linguistics, COLING
2022
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B. Xiong, N. Potyka, T. Tran, M. Nayyeri and S. Staab, Faithful Embeddings for EL++) Knowledge Bases, in: The Semantic Web - ISWC 2022 - 21st International Semantic Web Conference, Virtual Event, October 23-27, 2022, Proceedings
2022
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2022
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B. Xiong, N. Potyka, T. Tran, M. Nayyeri and S. Staab, Faithful Embeddings for EL++ ) Knowledge Bases, in: The Semantic Web - ISWC 2022 - 21st International Semantic Web Conference, Virtual Event, October 23-27, 2022, Proceedings
2022
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2022
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M. Ali, M. Berrendorf, C.T. Hoyt, L. Vermue, M. Galkin, S. Sharifzadeh, A. Fischer, V. Tresp and J. Lehmann, Bringing Light Into the Dark: A Large-Scale Evaluation of Knowledge Graph Embedding Models Under a Unified Framework, IEEE Trans. Pattern Anal. Mach. Intell
2022
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M. Baumgartner, D. Dell’Aglio, H. Paulheim and A. Bernstein, Towards the Web of Embeddings: Integrating multiple knowledge graph embedding spaces with FedCoder, J. Web Semant
2022
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J.Z. Pan, S. Razniewski, J.-C. Kalo, S. Singhania, J. Chen, S. Dietze, H. Jabeen, J. Omeliyanenko, W. Zhang, M. Lissandrini, R. Biswas, G. de Melo, A. Bonifati, E. Vakaj, M. Dragoni and D. Graux, Large Language Models and Knowledge Graphs: Opportunities and Challenges, Transactions on Graph Data and Knowledge
2023
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Y. Geng, J. Chen, J.Z. Pan, M. Chen, S. Jiang, W. Zhang and H. Chen, Relational Message Passing for Fully Inductive Knowledge Graph Completion, in: 39th IEEE International Conference on Data Engineering, ICDE 2023, Anaheim, CA, USA, April 3-7, 2023
2023
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2023
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2023
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F.M. Suchanek and A.T. Luu, Knowledge Bases and Language Models: Complementing Forces, in: Rules and Reasoning - 7th International Joint Conference, RuleML+RR 2023, Oslo, Norway, September 18-20, 2023, Proceedings
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2023
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2023
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S. Pan, L. Luo, Y. Wang, C. Chen, J. Wang and X. Wu, Unifying large language models and knowledge graphs: A roadmap, IEEE Transactions on Knowledge and Data Engineering
2024
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M. Jackermeier, J. Chen and I. Horrocks, Dual box embeddings for the description logic EL++, in: Proceedings of the International Conference on World Wide Web
2024
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D.Q. Nguyen, T.D. Nguyen, D.Q. Nguyen and D.Q. Phung, A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network, in: Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT
2053
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R. Zhang, F. Kong, C. Wang and Y. Mao, Embedding of Hierarchically Typed Knowledge Bases, in: Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, (AAAI-18), the 30th innovative Applications of Artificial Intelligence (IAAI-18), and the 8th AAAI Symposium on Educational Advances in Artificial Intelligence (EAAI-18)
2053
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T. Trouillon, J. Welbl, S. Riedel, E. Gaussier and G. Bouchard, Complex Embeddings for Simple Link Prediction, in ICML’16
2080
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