Research Papers Related to Knowledge Graph Reasoning

TOC

• 1. Survey
• 2. Neural
  • 2.1. Translation-based
  • 2.2. Tensor Decomposition
  • 2.3. Neural Network
• 3. Symbolic
• 4. Neural-Symbolic
• 5. Other Topics
  • 5.1. Open set
  • 5.2. Sparse KG
  • 5.3. Few-shot
  • 5.4. Commonsense Knowledge Graph Completion
• 6. Evaluation

Scholar

• Jian Tang [homepage]

1. Survey

• Knowledge Graph Completion: A Review. IEEE Access. 2020. [paper]
• CoDEx: A Comprehensive Knowledge Graph Completion Benchmark. EMNLP. 2020. [paper]
• Neural, Symbolic and Neural-Symbolic Reasoning on Knowledge Graphs. AI Open. 2021. [paper]

2. Neural

2.1. Translation-based

• [TransE] Translating embeddings for modeling multi-relational data. NeurIPS. 2013. [paper]
  • [TransH] Knowledge graph embedding by translating on hyperplanes. AAAI. 2014. [paper]
  • [TransR] Learning Entity and Relation Embeddings for Knowledge Graph Completion. AAAI. 2015. [paper]
  • [TransD] Knowledge Graph Embedding via Dynamic Mapping Matrix. ACL. 2015. [paper]
• [RotatE] RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space. ICLR.2018. [paper]

2.2. Tensor Decomposition

• [RESCAL] Factorizing YAGO: scalable machine learning for linked data. WWW. 2012. [paper]
• [DistMult] Embedding Entities and Relations for Learning and Inference in Knowledge Bases. ICLR. 2015. [paper]
  • [ComplEx] Complex Embeddings for Simple Link Prediction. ICML. 2016. [paper]
    • Canonical Tensor Decomposition for Knowledge Base Completion. ICML. 2018. [paper]
• [SimplE] SimplE Embedding for Link Prediction in Knowledge Graphs. NeurlPS. 2018. [paper]
  • [CP] The expression of a tensor or a polyadic as a sum of products. Studies in Applied Mathematics.1927. [paper]
  • Knowledge Base Completion: Baselines Strike Back. Rep4NLP@ACL. 2017. [paper]
• [TuckER] TuckER: Tensor Factorization for Knowledge Graph Completion. EMNLP. 2019. [paper]

2.3. Neural Network

• [ConvE] Convolutional 2D Knowledge Graph Embeddings. AAAI. 2018. [paper]
• [ConvKB] A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network. NAACL-HLT. 2018. [paper]
• [SACN] End-to-end Structure-Aware Convolutional Networks for Knowledge Base Completion. AAAI. 2018. [paper]
• Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs. ACL. 2019. [paper]
• A2N: Attending to Neighbors for Knowledge Graph Inference. ACL. 2019. [paper]
• [RGHAT] Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion. AAAI. 2020. [paper]

3. Symbolic

• [ProPPR] Efficient inference and learning in a large knowledge base. Machine Learning. 2015. [paper]
• [AMIE] AMIE: association rule mining under incomplete evidence in ontological knowledge bases. WWW. 2013. [paper]
  • [AMIE+] Fast rule mining in ontological knowledge bases with AMIE+. VLDB. 2015. [paper]
  • [AMIE3] Fast and Exact Rule Mining with AMIE 3. ESWC. 2020. [paper]
• [RUDIK] Robust Discovery of Positive and Negative Rules in Knowledge Bases. ICDE. 2018. [paper]
• [RLvLR] Scalable Rule Learning via Learning Representation. IJCAI. 2018. [paper]

4. Neural-Symbolic

• [PRA] Random Walk Inference and Learning in A Large Scale Knowledge Base. EMNLP. 2011. [paper]
• [SFE] Efficient and Expressive Knowledge Base Completion Using Subgraph Feature Extraction. EMNLP. 2015. [paper]
• [Path-RNN] Compositional Vector Space Models for Knowledge Base Completion. ACL. 2015. [paper]
  • Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks. EACL. 2017. [paper]
• [CPRA] Knowledge Base Completion via Coupled Path Ranking. ACL. 2016. [paper]
• [DeepPath] DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning. EMNLP. 2017. [paper]
• [AnyBURL] Anytime Bottom-Up Rule Learning for Knowledge Graph Completion. IJCAI. 2019. [paper]
• [pLogic] Probabilistic Logic Neural Networks for Reasoning. NeurIPS. 2019. [paper]
• [IterE] Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning. WWW. 2019. [paper]
• [pGAT] Probabilistic Logic Graph Attention Networks for Reasoning. WWW. 2020. [paper]

5. Other Topics

5.1. Open set

• [ConMask] Open-World Knowledge Graph Completion. AAAI. 2018. [paper]
• [OWE] An Open-World Extension to Knowledge Graph Completion Models. AAAI. 2019. [paper]

5.2. Sparse KG

• [DacKGR] Dynamic Anticipation and Completion for Multi-Hop Reasoning over Sparse Knowledge Graph. EMNLP. 2020. [paper]

5.3. Few-shot

• Few-Shot Knowledge Graph Completion. AAAI. 2020. [paper]

5.4. Commonsense Knowledge Graph Completion

6. Evaluation

• Realistic Re-evaluation of Knowledge Graph Completion Methods: An Experimental Study. SIGMOD. 2020. [paper]
• You CAN Teach an Old Dog New Tricks! On Training Knowledge Graph Embeddings. ICLR. 2020. [paper]