TY - GEN
T1 - CAb-NC
T2 - 11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019
AU - Kimura, Masaomi
N1 - Publisher Copyright:
© 2019 Association for Computing Machinery.
PY - 2019/8/27
Y1 - 2019/8/27
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85078868398&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85078868398&partnerID=8YFLogxK
U2 - 10.1145/3341161.3342944
DO - 10.1145/3341161.3342944
M3 - Conference contribution
AN - SCOPUS:85078868398
T3 - Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019
SP - 538
EP - 539
BT - Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019
A2 - Spezzano, Francesca
A2 - Chen, Wei
A2 - Xiao, Xiaokui
PB - Association for Computing Machinery, Inc
Y2 - 27 August 2019 through 30 August 2019
ER -