From complex network to skeleton: M j -Modified topology potential for node importance identification

Hanning Yuan, Kanokwan Malang*, Yuanyuan Lv, Aniwat Phaphuangwittayakul

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

3 引用 (Scopus)

摘要

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.

源语言英语
主期刊名Advanced Data Mining and Applications - 14th International Conference, ADMA 2018, Proceedings
编辑Guojun Gan, Xue Li, Shuliang Wang, Bohan Li
出版商Springer Verlag
413-427
页数15
ISBN(印刷版)9783030050894
DOI
出版状态已出版 - 2018
活动14th International Conference on Advanced Data Mining and Applications, ADMA 2018 - Nanjing, 中国
期限: 16 11月 201818 11月 2018

出版系列

姓名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
11323 LNAI
ISSN(印刷版)0302-9743
ISSN(电子版)1611-3349

会议

会议14th International Conference on Advanced Data Mining and Applications, ADMA 2018
国家/地区中国
Nanjing
时期16/11/1818/11/18

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