Must-read papers on Knowledge Graph Reasoning (KGR)

Content

1. Logical Rules
1.1 Logical Query	1.2 Rule Mining
1.3 Others
2. Relational Paths
2.1 Path Ranking	2.2 Path Constraints
2.3 Sequential Decision

Logical Rules

Logical Query

1. Embedding Logical Queries on Knowledge Graphs. NIPS 2018. Will Hamilton, Payal Bajaj, Marinka Zitnik, Dan Jurafsky, Jure Leskovec. [Paper] [Code]

2. Query2box: Reasoning over Knowledge Graphs in Vector Space Using Box Embedding. ICLR 2020. Hongyu Ren, Weihua Hu, Jure Leskovec. [Paper]

Rule Mining

1. AMIE: association rule mining under incomplete evidence in ontological knowledge bases. WWW 2013. Luis Galárraga, Christina Teflioudi, Katja Hose, Fabian M. Suchanek. [Paper]

2. Differentiable learning of logical rules for knowledge base reasoning. NIPS 2017. Yang, Fan and Yang, Zhilin and Cohen, William W. [Paper][code]

3. DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs. NeurIPS 2019. Ali Sadeghian, Mohammadreza Armandpour, Patrick Ding, Daisy Zhe Wang. [Paper] [Code]

Others

1. End-to-end differentiable proving. NIPS 2017. Rocktäschel, Tim and Riedel, Sebastian. [Paper][code]

2. Quantum Embedding of Knowledge for Reasoning. NeurIPS 2019. Dinesh Garg, Shajith Ikbal, Santosh K. Srivastava, Harit Vishwakarma, Hima Karanam, L Venkata Subramaniam. [Paper] [Code]

3. Probabilistic logic neural networks for reasoning. NeurIPS 2019. Meng Qu, Jian Tang. [Paper] [Code]

Relational Paths

Path Ranking

1. Random walk inference and learning in a large scale knowledge base. EMNLP 2011. Ni Lao, Tom Mitchell, William W. Cohen. [Paper]

2. DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning. EMNLP 2017. Wenhan Xiong, Thien Hoang, William Yang Wang. [Paper] [Code]

Path Constraints

1. Traversing Knowledge Graphs in Vector Space. EMNLP 2015. Kelvin Guu, John Miller, Percy Liang. [Paper]

2. PTransE: Modeling Relation Paths for Representation Learning of Knowledge Bases. EMNLP 2015. Yankai Lin, Zhiyuan Liu, Huanbo Luan, Maosong Sun, Siwei Rao, Song Liu. [Paper] [Code]

3. Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs. ICML 2019. Lingbing Guo, Zequn Sun, Wei Hu. [Paper]

Sequential Decision

1. Go for a Walk and Arrive at the Answer: Reasoning Over Paths in Knowledge Bases using Reinforcement Learning. ICLR 2018. Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alex Smola, Andrew McCallum. [Paper]

2. M-Walk: Learning to Walk over Graphs using Monte Carlo Tree Search. NIPS 2018. Yelong Shen, Jianshu Chen, Po-Sen Huang, Yuqing Guo, Jianfeng Gao. [Paper]

3. Multi-Hop Knowledge Graph Reasoning with Reward Shaping. EMNLP 2018. Xi Victoria Lin, Richard Socher, Caiming Xiong. [Paper]

4. Dynamically Pruned Message Passing Networks for Large-scale Knowledge Graph Reasoning. ICLR 2020. Xiaoran Xu, Wei Feng, Yunsheng Jiang, Xiaohui Xie, Zhiqing Sun, Zhi-Hong Deng. [Paper]