A novel metric for edge centrality

Xiaodi Huang, Muxiong Huang, Weidong Huang

Research output: Book chapter/Published conference paperConference paperpeer-review

1 Citation (Scopus)


As we are in the age of big data, graph data become bigger. A big graph normally has the overwhelming numbers of edges. Existing metrics of edge centrality are not suitable for dealing with such a large graph. A novel metric for measuring the importance of edges in a graph is presented. This metric not only captures the structural feature of a graph, but also has the good scalability. The extensive experiments have demonstrated the performance of the proposed metric by comparing it with several popular metrics against real-world graphs.
Original languageEnglish
Title of host publicationBDIOT 2017
Subtitle of host publicationProceedings of the international conference on big data and internet of things
PublisherAssociation for Computing Machinery
Number of pages5
ISBN (Electronic)9781450354301
Publication statusPublished - 20 Dec 2017
Event2017 International Conference on Big Data and Internet of Things: BDIOT 2017 - Novotel London Blackfriars Hotel, London, United Kingdom
Duration: 20 Dec 201722 Dec 2017
http://www.bdiot.org/2017.html (Conference website)
https://web.archive.org/web/20170728085253/http://www.bdiot.org:80/index.html (Conference website)


Conference2017 International Conference on Big Data and Internet of Things
Country/TerritoryUnited Kingdom
OtherThe main purpose of BDIOT 2017 is to provide an international platform for presenting and publishing the latest scientific research outcomes related to the topics of Big Data and Internet of Thing. This conference offers good opportunities for the delegates to exchange new ideas, and to establish research and/or business links, as well as to build global partnership for potential collaboration. We sincerely hope that the conference will help advance knowledge in relevant scientific and academic fields.
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