Graph-theoretic node importance mining in world city networks: methods and applications

Abstract

Purpose

This study aims to review the literature on graph-theoretic mining methods for node importance in both static and dynamic world city networks, which is correspondingly categorised by graph-theoretic node importance mining on network topologies and transmission mechanisms.

Design/methodology/approach

The authors overview the graph-theoretic indicators of node importance: centrality and power. Then, the methods of graph-theoretic node importance mining on network topologies are assessed with node relevance, centrality- and power-based measurements, heterogeneous fusion and other miscellaneous approaches. The latest progress in transmission mechanisms is also reviewed in this study involving network evolution, node immunisation and robustness in dynamics. Finally, the findings are analysed and future directions in this field are suggested.

Findings

The method development of node importance mining is driven by complex application-based problems within a transmission mechanism. Fusion measurements, based on centrality and power, are extended by other graph mining techniques in which power has a significant role. In conclusion, the trends of node importance mining focus on power-embedded fusion measurements in the transmission mechanism-based complex applications.

Originality/value

This is the first systematic literature review of node importance from the view of graph-theoretic mining.

Citation

Xue, S., Xiong, L., Lu, Z. and Wu, J. (2017), "Graph-theoretic node importance mining in world city networks: methods and applications", Information Discovery and Delivery, Vol. 45 No. 2, pp. 57-65. https://doi.org/10.1108/IDD-09-2016-0032