@inproceedings{6cb26254b6e944048669db19d9ae506a,
title = "From complex network to skeleton: M j -Modified topology potential for node importance identification",
abstract = " Node importance identification is a crucial content in studying the substantial information and the inherent behaviors of complex network. On the basis of topological characteristics of nodes in complex network, we introduce the idea of topology potential from data field theory to capture the important nodes and view it as the skeleton nodes. Inspired by an assumption that different mass of node (m j parameter) reflects different quality and interaction reliability over the network space. We propose TP-KS method that is an improved topology potential algorithm whose m j is identified by k-shell centrality. The important nodes identified by TP-KS is ranked and verified by SIR epidemic spreading model. Through the theoretical and experimental analysis, it is proved that TP-KS can effectively extract the importance of nodes in complex network. The better results from TP-KS are also confirmed in both real-world networks and artificial random scale-free networks.",
keywords = "Complex network, Node importance evaluation, Skeleton network, Topology potential",
author = "Hanning Yuan and Kanokwan Malang and Yuanyuan Lv and Aniwat Phaphuangwittayakul",
note = "Publisher Copyright: {\textcopyright} 2018, Springer Nature Switzerland AG.; 14th International Conference on Advanced Data Mining and Applications, ADMA 2018 ; Conference date: 16-11-2018 Through 18-11-2018",
year = "2018",
doi = "10.1007/978-3-030-05090-0_35",
language = "English",
isbn = "9783030050894",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "413--427",
editor = "Guojun Gan and Xue Li and Shuliang Wang and Bohan Li",
booktitle = "Advanced Data Mining and Applications - 14th International Conference, ADMA 2018, Proceedings",
address = "Germany",
}