Multilevel network alignment

Si Zhang, Ross Maciejewski, Hanghang Tong, Tina Eliassi-Rad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Network alignment, which aims to find the node correspondence across multiple networks, is a fundamental task in many areas, ranging from social network analysis to adversarial activity detection. The state-of-the-art in the data mining community often view the node correspondence as a probabilistic cross-network node similarity, and thus inevitably introduce an Ω (n2 ) lower bound on the computational complexity. Moreover, they might ignore the rich patterns (e.g., clusters) accompanying the real networks. In this paper, we propose a multilevel network alignment algorithm (Moana) which consists of three key steps. It first efficiently coarsens the input networks into their structured representations, and then aligns the coarsest representations of the input networks, followed by the interpolations to obtain the alignment at multiple levels including the node level at the finest granularity. The proposed coarsen-align-interpolate method bears two key advantages. First, it overcomes the Ω (n2 ) lower bound, achieving a linear complexity. Second, it helps reveal the alignment between rich patterns of the input networks at multiple levels (e.g., node, clusters, super-clusters, etc.). Extensive experimental evaluations demonstrate the efficacy of the proposed algorithm on both the node-level alignment and the alignment among rich patterns (e.g., clusters) at different granularities.

Original languageEnglish (US)
Title of host publicationThe Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019
PublisherAssociation for Computing Machinery, Inc
Pages2344-2354
Number of pages11
ISBN (Electronic)9781450366748
DOIs
StatePublished - May 13 2019
Event2019 World Wide Web Conference, WWW 2019 - San Francisco, United States
Duration: May 13 2019May 17 2019

Publication series

NameThe Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019

Conference

Conference2019 World Wide Web Conference, WWW 2019
CountryUnited States
CitySan Francisco
Period5/13/195/17/19

Fingerprint

Electric network analysis
Data mining
Computational complexity
Interpolation

Keywords

  • Multilevel alignment
  • Multiresolution
  • Network alignment

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

Cite this

Zhang, S., Maciejewski, R., Tong, H., & Eliassi-Rad, T. (2019). Multilevel network alignment. In The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019 (pp. 2344-2354). (The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019). Association for Computing Machinery, Inc. https://doi.org/10.1145/3308558.3313484

Multilevel network alignment. / Zhang, Si; Maciejewski, Ross; Tong, Hanghang; Eliassi-Rad, Tina.

The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019. Association for Computing Machinery, Inc, 2019. p. 2344-2354 (The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhang, S, Maciejewski, R, Tong, H & Eliassi-Rad, T 2019, Multilevel network alignment. in The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019. The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019, Association for Computing Machinery, Inc, pp. 2344-2354, 2019 World Wide Web Conference, WWW 2019, San Francisco, United States, 5/13/19. https://doi.org/10.1145/3308558.3313484
Zhang S, Maciejewski R, Tong H, Eliassi-Rad T. Multilevel network alignment. In The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019. Association for Computing Machinery, Inc. 2019. p. 2344-2354. (The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019). https://doi.org/10.1145/3308558.3313484
Zhang, Si ; Maciejewski, Ross ; Tong, Hanghang ; Eliassi-Rad, Tina. / Multilevel network alignment. The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019. Association for Computing Machinery, Inc, 2019. pp. 2344-2354 (The Web Conference 2019 - Proceedings of the World Wide Web Conference, WWW 2019).
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