@inproceedings{f1c7232a350c4911912ede2ab4e9dfce,
title = "A Label-Based Nature Heuristic Algorithm for Dynamic Community Detection",
abstract = "The evolving patterns of the real-world can be tracked and captured by the dynamic network community structure. Some existing methods such as the multi-objective particle swarm optimization (MOPSO) use the evolutionary clustering model to detect the dynamic network community. However, the MOPSO has defects that are undesirable premature convergence and insufficient diversity of particles due to a high selection pressure. Therefore, a label-based heuristic algorithm based on the evolutionary clustering model is proposed for overcoming those shortcomings. The label propagation algorithm is adopted to initialize community structure and restrict the condition of the mutation process. The operations of crossover and mutation are used to increase the diversity of solutions and maintain the quality of community structure simultaneously. Experimental results demonstrate that the proposed method is effective and outperforms other methods in synthetic and real-world datasets.",
keywords = "Community structure, Dynamic networks, Label propagation, Nature-inspired algorithm",
author = "Chunyu Wang and Yue Deng and Xianghua Li and Yingchu Xin and Chao Gao",
note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 16th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2019 ; Conference date: 26-08-2019 Through 30-08-2019",
year = "2019",
doi = "10.1007/978-3-030-29911-8\_48",
language = "英语",
isbn = "9783030299101",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "621--632",
editor = "Nayak, \{Abhaya C.\} and Alok Sharma",
booktitle = "PRICAI 2019",
}