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Identification of node influence based on improved k-shell algorithm

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Nodes that have greater influence in complex networks play an important role in controlling rumors propagation, optimizing resource allocation, spreading information efficiently, and advertising accurately. In view of the current many methods in identifying the node's influence had certain limitation, this paper based on the k-shell algorithm defined the concept of weighted degree, and putted forward the Modified K-shell Algorithm, shorted for MKS algorithm by measuring the potential importance of edges and considering the different contributions of neighbors. This algorithm considers the nodes' own features, location features and local features. Through implementing this algorithm on the representative Zachary karate club network and comparing with other typical methods, it is found that this algorithm improves the coarse division of k-shell algorithm, and its result is more reasonable.

Original languageEnglish
Title of host publicationProceedings of 2019 IEEE 1st International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2019
EditorsHuabo Sun
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages262-266
Number of pages5
ISBN (Electronic)9781728125985
DOIs
StatePublished - Oct 2019
Externally publishedYes
Event1st IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2019 - Kunming, China
Duration: 17 Oct 201919 Oct 2019

Publication series

NameProceedings of 2019 IEEE 1st International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2019

Conference

Conference1st IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2019
Country/TerritoryChina
CityKunming
Period17/10/1919/10/19

Keywords

  • Complex networks
  • Influence identification
  • K-shell
  • Weighted degree

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