@inproceedings{e9fcb68dec8548fd9f5189f0ee2cb35b,
title = "CAb-NC: The correspondence analysis based network clustering method",
abstract = "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{\textquoteright}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{\textquoteright} coordinates and discussed its equivalence to spectral clustering and its relationship to Newman{\textquoteright}s modularity.",
author = "Masaomi Kimura",
year = "2019",
month = aug,
day = "27",
doi = "10.1145/3341161.3342944",
language = "English",
series = "Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019",
publisher = "Association for Computing Machinery, Inc",
pages = "538--539",
editor = "Francesca Spezzano and Wei Chen and Xiaokui Xiao",
booktitle = "Proceedings of the 2019 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019",
note = "11th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2019 ; Conference date: 27-08-2019 Through 30-08-2019",
}