Online Community Detection for Large Complex Networks
Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence. Pages 1903-1908.
Abstract
Complex networks describe a wide range of systems in nature and society. To understand the complex networks, it is crucial to investigate their internal structure. In this paper, we propose an online community detection method for large complex networks, which make it possible to process networks edge-by-edge in a serial fashion. We investigate the generative mechanism of complex networks and propose a split mechanism based on the degree of the nodes to create new community. Our method has linear time complexity. The method has been applied to six real-world network datasets and the experimental results show that it is comparable to existing methods in modularity with much less running time.
@inproceedings{ijcai2013p281,
title = {Online Community Detection for Large Complex Networks},
author = {Zhang, Wangsheng and Pan, Gang and Wu, Zhaohui and Li, Shijian},
booktitle = {Proceedings of the Twenty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-13}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Francesca Rossi},
pages = {1903--1908},
year = {2013},
month = {8},
url = {https://ijcai.org/proceedings/2013/281},
}
TY - CPAPER TI - Online Community Detection for Large Complex Networks AU - Zhang, Wangsheng AU - Pan, Gang AU - Wu, Zhaohui AU - Li, Shijian T2 - Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2013 SP - 1903 EP - 1908 UR - https://ijcai.org/proceedings/2013/281 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
