DeepMatching: A Structural Seed Identification Framework for Social Network Alignment

@article{Wang2018DeepMatchingAS,
  title={DeepMatching: A Structural Seed Identification Framework for Social Network Alignment},
  author={Chenxu Wang and Zhiyuan Zhao and Yuhuai Wang and Dong Qin and Xiapu Luo and Tao Qin},
  journal={2018 IEEE 38th International Conference on Distributed Computing Systems (ICDCS)},
  year={2018},
  pages={600-610}
}
Network alignment aims at finding a bijective mapping between nodes of two networks. Due to its wide application in various fields (e.g., Computer Vision, Data Management, Bioinformatics, and Privacy Protection), researchers have proposed many network alignment algorithms, most of which rely on a set of pre-mapped seeds. However, it is challenging to identify an initial credible set of seeds solely with structural information. In this paper, by exploiting the observation that a true mapping… CONTINUE READING

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SHOWING 1-10 OF 57 REFERENCES

Point Set Registration: Coherent Point Drift

  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • 2010
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

De-anonymizing social networks and inferring private attributes using knowledge graphs

  • IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications
  • 2016
VIEW 1 EXCERPT

On the relative de-anonymizability of graph data: Quantification and evaluation

  • IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications
  • 2016
VIEW 2 EXCERPTS