Characterization and graph embedding of weighted social networks through Diffusion Wavelets

Zhiliang Chen, Junfeng Wu, Huakang Li, Guozi Sun

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)

Abstract

More and more graph embedding algorithms have been proposed, which makes the similarity judgment of graph structure more and more accurate. While exploring the similarity of neighborhood structures, the existence of weights should also be taken into account, so as to reflect the relational social network graph in the real world. We use Graphwave, a kind of algorithms for graph embedding with diffusion wavelets, to incorporate weight into numerical value to calculate, and to process the returned probability distribution parameters, so that we can get some analysis about the actual complex network. Our analysis can overcome the priori misjudgment problem based on the topological structure, and then obtain the actual similarity of the network structure from the results of graph embedding.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019
EditorsChaitanya Baru, Jun Huan, Latifur Khan, Xiaohua Tony Hu, Ronay Ak, Yuanyuan Tian, Roger Barga, Carlo Zaniolo, Kisung Lee, Yanfang Fanny Ye
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5346-5352
Number of pages7
ISBN (Electronic)9781728108582
DOIs
Publication statusPublished - Dec 2019
Externally publishedYes
Event2019 IEEE International Conference on Big Data, Big Data 2019 - Los Angeles, United States
Duration: 9 Dec 201912 Dec 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Big Data, Big Data 2019

Conference

Conference2019 IEEE International Conference on Big Data, Big Data 2019
Country/TerritoryUnited States
CityLos Angeles
Period9/12/1912/12/19

Keywords

  • Weighted relationship
  • graph embedding
  • graph-wave
  • social network

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