Temporal-Aware Knowledge Resource: Paper

Here, we are concentrate on collection of research papers involving temporal-aware topics, including temporal rule learning and resoning, temporal relation extraction, temporal text mining, deep spatial-temporal graph modeling, embedding learning of temporal knowledge graph, temporal knowledge graph curation and visulization, temporal commonsense understanding.

Table of Contents

• Survey
• Temporal Rule Learning and Resoning
• Temporal Relation Extraction
• Temporal Relation Checking
• Temporal Text Mining
• Event-Centric Temporal Knowledge Graph
• Evolution Analysis and Prediction based Event
• Deep Spatial-Temporal Graph Modeling
• Embedding Learning of Temporal Knowledge Graph
• Temporal Knowledge Graph Curation and Visulization
• Temporal Commonsense Understanding
• Thesis

Survey

1. Siddhant Arora. A Survey on Graph Neural Networks for Knowledge Graph Completion. Arxiv 2020. [Paper] [《图神经网络知识图谱补全》 (Interpreted in Chinese)]

2. Yu Xie, Chunyi Li, Bin Yu, Chen Zhang, Zhouhua Tang. A Survey on Dynamic Network Embedding. Arxiv 2020. [Paper]

3. Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, Philip S. Yu. A Survey on Knowledge Graphs: Representation, Acquisition and Applications. Arxiv 2020. [Paper]

4. Dat Quoc Nguyen. An overview of embedding models of entities and relationships for knowledge base completion. Arxiv 2020. [Paper]

5. Seyed Mehran Kazemi, Rishab Goel, Kshitij Jain, Ivan Kobyzev, Akshay Sethi, Peter Forsyth, Pascal Poupart. Relational Representation Learning for Dynamic (Knowledge) Graphs: A Survey. Arxiv 2019. [Paper]

Temporal_Rule_Learning_and_Resoning

1. Woojeong Jin, He Jiang, Meng Qu, Tong Chen, Changlin Zhang, Pedro Szekely, Xiang Ren. Recurrent Event Network for Reasoning over Temporal Knowledge Graphs. ICLR 2019. [Paper][Code]

2. Tanya Goyal, Greg Durrett. Embedding time expressions for deep temporal ordering models. Arxiv 2019. [Paper]

3. Pouya Ghiasnezhad Omran, Kewen Wang, Zhe Wang. Learning Temporal Rules from Knowledge Graph Streams. AAAI 2019. [Paper]

4. Boyi Hou, Youcef Nafa. Enabling Temporal Reasoning for Fact Statements: A Web-Based Approach. DASFAA 2018. [Paper]

5. Chekol, Melisachew Wudage, Pirrò, Giuseppe, Schönfisch, Jörg, Stuckenschmidt, Heiner. Marrying Uncertainty and Time in Knowledge Graphs. AAAI 2017. [Paper]

6. Rakshit Trivedi, Hanjun Dai, Yichen Wang, Le Song. Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs. ICML 2017. [Paper][Code]

7. Yafang Wang, Mohamed Yahya, Martin Theobald. Time-aware Reasoning in Uncertain Knowledge Bases. VLDB 2010. [Paper]

Temporal_Relation_Extraction

1. Qiang Ning, Sanjay Subramanian, Dan Roth. An Improved Neural Baseline for Temporal Relation Extraction . EMNLP 2019. [Paper]

2. Rujun Han, Qiang Ning, Nanyun Peng. Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction. EMNLP 2019. [Paper]

3. Partha Pratim Talukdar, Derry Wijaya, Tom Mitchell. Acquiring temporal constraints between relations. CIKM 2012. [Paper]

Temporal_Relation_Checking

1. Partha Pratim Talukdar, Derry Wijaya, Tom Mitchell. Coupled Temporal Scoping of Relational Facts. WSDM 2012. [Paper]

Temporal_Text_Mining

1. Junsha Chen, Neng Gao, Cong Xue, Chenyang Tu, Daren Zha. Perceiving Topic Bubbles: Local Topic Detection in Spatio-Temporal Tweet Stream. DASFAA 2019. [Paper]

2. Shuai Xu, Jiuxin Cao, Xuelin Zhu, Yi Dong, Bo Liu. Community Discovery Based on Social Relations and Temporal-Spatial Topics in LBSNs. PAKDD 2018. [Paper]

3. Yafang Wang, Zhaochuan Ren, Martin Theobald, Maximilian Dylla, Gerard de Melo. Summary Generation for Temporal Extractions. DEXA 2016. [Paper]

4. Yafang Wang, Maximilian Dylla, Marc Spaniol and Gerhard Weikum. Coupling Label Propagation and Constraints for Temporal Fact Extraction. ACL 2012. [Paper]

5. Yafang Wang, Bin Yang, Spyros Zoupanos, Marc Spaniol, Gerhard Weikum. Scalable Spatio-temporal Knowledge Harvesting. WWW 2011. [Paper]

6. Yafang Wang, Mingjie Zhu, Lizhen Qu, Marc Spaniol, Gerhard Weikum. Timely YAGO: Harvesting, Querying, and Visualizing Temporal Knowledge from Wikipedia. ECBT 2010. [Paper]

7. Qiaozhu Mei, Chengxiang Zhai. Discovering Evolutionary Theme Patterns from Text - An Exploration of Temporal Text Mining. ACM SIGKDD 2005. [Paper]

Event_Centric_Temporal_Analysis

1. Dinesh Raghu, Surag Nair, Mausam. Inferring Temporal Knowledge for Near-Periodic Recurrent Events. IJCAI 2018. [Paper]

2. Simon Gottschalk, Elena Demidova. EventKG: A Multilingual Event-Centric Temporal Knowledge Graph. ESWC 2018. [Paper]

Evolution_Analysis_and_Prediction_based_Event

1. Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, Xiaojun Chang, Chengqi Zhang. Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks. KDD 2020. [Paper]

2. Jiaqi Liu, Qin Zhang, Luoyi Fu, Xinbing Wang, Songwu Lu. Evolving Knowledge Graphs. Infocom 2019. [Paper]

3. Crist´obal Esteban, Volker Tresp, Yinchong Yang, Stephan Baier, Denis Krompaß. Predicting the Co-Evolution of Event and Knowledge Graphs. Fusion 2016. [Paper]

4. 邱均平, 李小涛. 基于引文网络挖掘和时序分析的知识扩散研究. 计算机研究与发展 2017. [Paper]

5. Nathanael Chambers, Taylor Cassidy, Bill McDowell, Steven Bethard. Dense Event Ordering with a Multi-Pass Architecture. TACL 2014. [Paper]

Deep_Spatial-Temporal_Graph_Modeling

1. Emanuele Rossi, Ben Chamberlain, Fabrizio Frasca, and Davide Eynard. Temporal Graph Networks for Deep Learning on Dynamic Graphs. Arxiv 2020. [Paper] [PPT] [Video]

2. Yang Li, Buyue Qian, Xianli Zhang, and Hui Liu. Knowledge guided diagnosis prediction via graph spatial-temporal network. ICDM 2020. [Paper]

3. Da Xu, Chuanwei Ruan, Evren Korpeoglu, Sushant Kumar, and Kannan Achan. Inductive representation learning on temporal graphs. ICLR 2020. [Paper]

4. Zonghan Wu, Shirui Pan, Guodong Long, Jing Jiang, and Chengqi Zhang. Graph WaveNet for Deep Spatial-Temporal Graph Modeling. IJCAI 2019. [Paper][Code]

5. Woojeong Jin, He Jiang, Meng Qu, Tong Chen, Changlin Zhang, Pedro Szekely, and Xiang Ren. Recurrent Event Network: Global Structure Inference over Temporal Knowledge Graph. ICLR 2019. [Paper][Code]

6. Zhining Liu, Dawei Zhou, and Jingrui He. Towards Explainable Representation of Time-Evolving Graphs via Spatial-Temporal Graph Attention Networks. CIKM 2019. [Paper]

7. Zhendong Chu, Renqin Cai, and Hongning Wang. Accounting for Temporal Dynamics in Modeling Document Streams. CIKM 2019. [Paper]

8. Lei Bai, Lina Yao, Salil S. Kanhere, Xianzhi Wang, Wei Liu, and Zheng Yang. Spatio-Temporal Graph Convolutional and Recurrent Networks for Citywide Passenger Demand Prediction. CIKM 2019. [Paper]

9. Yuanfu Lu, Xiao Wang, Chuan Shi, Philip S.Yu, and Yanfang Ye. Temporal Network Embedding with Micro- and Macro-dynamics. Arxiv 2019. [Paper]

10. Aldo Pareja, Giacomo Domeniconi, Jie Chen, Tengfei Ma, Toyotaro Suzumura, Hiroki Kanezashi, Tim Kaler, Tao B.Schardl, and Charles E. Leiserson. EvolveGCN: Evolving Graph Convolutional Networks for Dynamic Graphs. Arxiv 2019. [Paper]

11. Yuan Zuo, Guannan Liu, Hao Lin, Jia Guo, Xiaoqian Hu, and Junjie Wu. Embedding Temporal Network via Neighborhood Formation. KDD 2018. [Paper]

Embedding_Learning_of_Temporal_Knowledge_Graph

1. Zhen Han, Yunpu Ma, Yuyi Wang, Stephan G¨unnemann, Volker Tresp Chenjin Xu, Mojtaba Nayyeri, Fouad Alkhoury, Hamed Yazdi, Jens Lehmann. Temporal Knowledge Graph Completion based on Time Series Gaussian Embedding. Arxiv 2020. [Paper]

2. Zhen Han, Yunpu Ma, Yuyi Wang, Stephan G¨unnemann, Volker Tresp. Graph Hawkes Neural Network for Forecasting on Temporal Knowledge Graphs. AKBC 2020. [Paper]

3. Timothée Lacroix, Guillaume Obozinski, Nicolas Usunier. Tensor Decompositions for temporal knowledge base completion. ICLR 2020. [Paper]

4. Rishab Goel, Seyed Mehran Kazemi, Marcus Brubaker, Pascal Poupart. Diachronic Embedding for Temporal Knowledge Graph Completion. AAAI 2020. [Paper]

5. Tianxing Wu, Arijit Khan, Huan Gao, Cheng Li. Efficiently Embedding Dynamic Knowledge Graphs. Arxiv 2019. [Paper]

6. Aravind Sankar, Yanhong Wu, Liang Gou, Wei Zhang, Hao Yang. Dynamic Graph Representation Learning via Self-Attention Networks. Workshop in ICLR 2019. [Paper][Code]

7. Rakshit Trivedi, Mehrdad Farajtabar, Prasenjeet Biswal, Hongyuan Zha. DYREP: Learning Representations over Dynamic Graphs. ICLR 2019. [Paper]

8. Boris Knyazev, Carolyn Augusta, Graham W. Taylor. Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions. Arxiv 2019. [Paper][Code]

9. Alberto Garc´ıa-Duran, Sebastijan Dumanciˇ c´, Mathias Niepert. Learning Sequence Encoders for Temporal Knowledge Graph Completion. EMNLP 2018. [Paper][Code]

10. Shib Sankar Dasgupta, Swayambhu Nath Ray, Partha Talukdar. HyTE: Hyperplane-based Temporally aware Knowledge Graph Embedding. EMNLP 2018. [Paper][Code]

11. Julien Leblay, Melisachew Wudage Chekol. Deriving Validity Time in Knowledge Graph. WWW 2018. [Paper]

12. Federico Bianchi, Matteo Palmonari, Debora Nozza. Towards Encoding Time in Text-Based Entity Embeddings. ISWC 2018. [Paper]

13. Tingsong Jiang, Tianyu Liu, Tao Ge, Lei Sha, Sujian Li, Baobao Chang, Zhifang Sui. Encoding Temporal Information for Time-Aware Link Prediction. EMNLP 2016. [Paper]

14. Tingsong Jiang, Tianyu Liu, Tao Ge, Lei Sha, Baobao Chang, Sujian Li, Zhifang Sui. Towards Time-Aware Knowledge Graph Completion. COLING 2016. [Paper]

15. Crist´obal Esteban, Volker Tresp, Yinchong Yang, Stephan Baier, Denis Krompaß. Predicting the Co-Evolution of Event and Knowledge Graphs. Arxiv 2015. [Paper]

16. 陈德华, 殷苏娜, 乐嘉锦, 王梅, 潘乔, 朱立峰. 一种面向临床领域时序知识图谱的链接预测模型. 计算机研究与发展 2017. [Paper]

三大顶会看动态图表示学习

图系列 # 7篇动态时空图网络学习必读的顶会论文

知识图谱 # 最近三年知识图谱在动态以及时间预测与补全上必读的6篇论文

论文导读 | TemporalGCN

论文浅尝 | 让“演进知识图谱”带你“瞻前顾后”看世界

【资源推荐】 时序处理文献/代码/数据集及相关资源大列表

Temporal_Knowledge_Graph_Curation_and_Visulization

1. Tong Ge, Yafang Wang, Gerard de Melo, Haofeng Li, Baoquan Chen. Visualizing and Curating Knowledge Graphs over Time and Space. ACL 2016. [Paper]

Temporal_QA

1. Camille Bourgaux, Anni-Yasmin Turhan. Temporal Query Answering in DL-Lite over Inconsistent Data. ISWC 2017. [Paper]

Temporal_Commonsense_Understanding

1. Ben Zhou, Daniel Khashabi, Qiang Ning, Dan Roth. “Going on a vacation” takes longer than “Going for a walk”: A Study of Temporal Commonsense Understanding. EMNLP 2019. [Paper]

Thesis

1. Yafang Wang. Methods and Tools for Temporal Knowledge Harvesting. Dissertation 2013. [Paper]