A Novel NMF Algorithm for Detecting Clusters in Directed Networks

Yoshito Usuzaka, Norikazu Takahashi

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

4 Citations (Scopus)

Abstract

Cluster detection is an important technique for a better understanding of the structure of a complex network. In this paper, we consider the problem of detecting clusters in directed networks. It is known that this problem can be formulated as an optimization problem in the form of nonnegative matrix factorization. Also, an iterative algorithm for solving the optimization problem has been developed. We derive a novel iterative algorithm for solving the same optimization problem, and experimentally evaluate the convergence rate and the cluster detection capability.

Original languageEnglish
Title of host publication2019 International Conference on Computing, Networking and Communications, ICNC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages148-152
Number of pages5
ISBN (Electronic)9781538692233
DOIs
Publication statusPublished - Apr 8 2019
Event2019 International Conference on Computing, Networking and Communications, ICNC 2019 - Honolulu, United States
Duration: Feb 18 2019Feb 21 2019

Publication series

Name2019 International Conference on Computing, Networking and Communications, ICNC 2019

Conference

Conference2019 International Conference on Computing, Networking and Communications, ICNC 2019
Country/TerritoryUnited States
CityHonolulu
Period2/18/192/21/19

Keywords

  • Cardano's method
  • cluster detection
  • directed network
  • nonnegative matrix factorization

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software
  • Hardware and Architecture

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