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Source Detection Method Based on Propagation Probability

  • Yuxin Ding*
  • , Longfei Wang
  • , Rui Wu
  • , Fuxing Xue
  • *Corresponding author for this work
  • Harbin Institute of Technology Shenzhen

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

Abstract

In this paper, we study how to locate network information sources given the propagation subgraph of information. We introduce the propagation probability into the complex network, which is used to describe the information transmission capability of the network nodes. The aim of the proposed model is to decrease the source locating error caused by the imbalance of information diffusion. We simulate the propagation of information in different types of complex networks. Experiments show that the propagation probability model can effectively improve the location accuracy.

Original languageEnglish
Title of host publicationCognitive Computing – ICCC 2018 - 2nd International Conference, Held as Part of the Services Conference Federation, SCF 2018, Proceedings
EditorsZhi-Hong Mao, Jing Xiao, Toyotaro Suzumura, Liang-Jie Zhang
PublisherSpringer Verlag
Pages179-186
Number of pages8
ISBN (Print)9783319943060
DOIs
StatePublished - 2018
Externally publishedYes
Event2nd International Conference on Cognitive Computing, ICCC 2018 Held as Part of the Services Conference Federation, SCF 2018 - Seattle, United States
Duration: 25 Jun 201830 Jun 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10971 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference2nd International Conference on Cognitive Computing, ICCC 2018 Held as Part of the Services Conference Federation, SCF 2018
Country/TerritoryUnited States
CitySeattle
Period25/06/1830/06/18

Keywords

  • Infection subgraph
  • Information source
  • Social network

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