G-CREWE: Graph CompREssion With Embedding for Network Alignment

@article{Qin2020GCREWEGC,
  title={G-CREWE: Graph CompREssion With Embedding for Network Alignment},
  author={Kyle Kai Qin and Flora D. Salim and Yongli Ren and Wei Shao and Mark Heimann and Danai Koutra},
  journal={Proceedings of the 29th ACM International Conference on Information \& Knowledge Management},
  year={2020}
}
  • K. K. Qin, Flora D. Salim, Danai Koutra
  • Published 30 July 2020
  • Computer Science
  • Proceedings of the 29th ACM International Conference on Information & Knowledge Management
Network alignment is useful for multiple applications that require increasingly large graphs to be processed. Existing research approaches this as an optimization problem or computes the similarity based on node representations. However, the process of aligning every pair of nodes between relatively large networks is time-consuming and resource-intensive. In this paper, we propose a framework, called G-CREWE (Graph CompREssion With Embedding) to solve the network alignment problem. G-CREWE uses… 

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