CAb-NC: The correspondence analysis based network clustering method

研究成果: Conference contribution

1 被引用数 (Scopus)

抄録

Finding clusters in a network has been practically important in many applications and was studied by many researchers. Most commonly used methods are spectral clustering and Newman’s modularity maximization. However, there has been no unified view of them. In this study, we introduced a new guiding principle based on correspondence analysis to obtain nodes’ coordinates and discussed its equivalence to spectral clustering and its relationship to Newman’s modularity.

本文言語English
ホスト出版物のタイトルProceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019
編集者Francesca Spezzano, Wei Chen, Xiaokui Xiao
出版社Association for Computing Machinery, Inc
ページ538-539
ページ数2
ISBN(電子版)9781450368681
DOI
出版ステータスPublished - 2019 8 27
イベント11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019 - Vancouver, Canada
継続期間: 2019 8 272019 8 30

出版物シリーズ

名前Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019

Conference

Conference11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019
国/地域Canada
CityVancouver
Period19/8/2719/8/30

ASJC Scopus subject areas

  • 通信
  • コンピュータ ネットワークおよび通信
  • 情報システムおよび情報管理
  • 社会学および政治科学

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