@inproceedings{b28acd4801f74867bb74bc5d7f71ff7a,
title = "Outlier detection for time-evolving complex networks",
abstract = "Complex systems have features such as numerous nodes and edges, complicated and hierarchical relations and evolving with time. During their running time, complex systems are influenced by the internal and external factors which can lead to abnormal states. Finding out the outliers can effectively supervise the whole system. Here, we study a real-world complex dynamic complex system, observe the abnormal pattern based on entropy, and find out nodes which will lead to the system collapse by GROD algorithm.",
keywords = "Complex system, Data mining, Dynamic graph, Outlier detection",
author = "Hong Zhang and Changzhen Hu and Xiaojun Wang",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2016.; 2nd International Conference on Electrical and Information Technologies for Rail Transportation, EITRT 2015 ; Conference date: 28-08-2015 Through 30-08-2015",
year = "2016",
doi = "10.1007/978-3-662-49370-0_70",
language = "English",
isbn = "9783662493687",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "677--684",
editor = "Yong Qin and Limin Jia and Lijun Diao and Jianghua Feng and Min An",
booktitle = "Proceedings of 2015 International Conference on Electrical and Information Technologies for Rail Transportation - Transportation",
address = "Germany",
}