Yunkai Lou

According to our database, Yunkai Lou authored at least 15 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Generalized Community-Structure-Aware Optimization Framework for Efficient Subgraph Matching in Social Network Analysis.

Yunkai Lou, Chaokun Wang

IEEE Trans. Comput. Soc. Syst., April, 2024

Towards a Converged Relational-Graph Optimization Framework.

Yunkai Lou, Longbin Lai, Bingqing Lyu, Yufan Yang, Xiaoli Zhou, Wenyuan Yu, Ying Zhang, Jingren Zhou

CoRR, 2024

A Graph-Native Query Optimization Framework.

Bingqing Lyu, Xiaoli Zhou, Longbin Lai, Yufan Yang, Yunkai Lou, Wenyuan Yu, Jingren Zhou

CoRR, 2024

Enhancing Neo4j Query Efficiency with Seamless Integration of the GOpt Optimization Framework.

Bingqing Lyu, Xiaoli Zhou, Longbin Lai, Yufan Yang, Yunkai Lou, Yongfei Liu

Proceedings of Workshops at the 50th International Conference on Very Large Data Bases, 2024

Temporal Graph Generation Featuring Time-Bound Communities.

Shuwen Zheng, Chaokun Wang, Cheng Wu, Yunkai Lou, Hao Feng, Xuran Yang

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

Incorporating Dynamic Temperature Estimation into Contrastive Learning on Graphs.

Ziyang Liu, Chaokun Wang, Liqun Yang, Yunkai Lou, Hao Feng, Cheng Wu, Kai Zheng, Yang Song

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

GraphHI: Boosting Graph Neural Networks for Large-Scale Graphs.

Hao Feng, Chaokun Wang, Ziyang Liu, Yunkai Lou, Zhenyu Liu, Xiaokun Zhu, Yongjun Bao, Weipeng Yan

Proceedings of the 40th IEEE International Conference on Data Engineering, 2024

2023

Time-topology analysis on temporal graphs.

Yunkai Lou, Chaokun Wang, Tiankai Gu, Hao Feng, Jun Chen, Jeffrey Xu Yu

VLDB J., July, 2023

Learning Adaptive Node Embeddings Across Graphs.

Gaoyang Guo, Chaokun Wang, Bencheng Yan, Yunkai Lou, Hao Feng, Junchao Zhu, Jun Chen, Fei He, Philip S. Yu

IEEE Trans. Knowl. Data Eng., June, 2023

Fast Unsupervised Graph Embedding via Graph Zoom Learning.

Ziyang Liu, Chaokun Wang, Yunkai Lou, Hao Feng

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022

HybridGNN: Learning Hybrid Representation in Multiplex Heterogeneous Networks.

Tiankai Gu, Chaokun Wang, Cheng Wu, Jingcao Xu, Yunkai Lou, Changping Wang, Kai Xu, Can Ye, Yang Song

CoRR, 2022

HybridGNN: Learning Hybrid Representation for Recommendation in Multiplex Heterogeneous Networks.

Tiankai Gu, Chaokun Wang, Cheng Wu, Yunkai Lou, Jingcao Xu, Changping Wang, Kai Xu, Can Ye, Yang Song

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

2021

Time-Topology Analysis.

Yunkai Lou, Chaokun Wang, Tiankai Gu, Hao Feng, Jun Chen, Jeffrey Xu Yu

Proc. VLDB Endow., 2021

2020

TinyGNN: Learning Efficient Graph Neural Networks.

Bencheng Yan, Chaokun Wang, Gaoyang Guo, Yunkai Lou

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

2019

OSMAC: Optimizing Subgraph Matching Algorithms with Community Structure.

Yunkai Lou, Chaokun Wang

Proceedings of the 35th IEEE International Conference on Data Engineering, 2019