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Mining Communities from Multi-Layered Graphs

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Chao, Meng
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Meng Chao (1.603Mb)
Abstract
Identifying communities from networks has been a subject of great interest in Biological and Social network analysis. Finding communities can help with tasks such as identifying and fighting disease. Using graphs to represent networks and identifying dense subgraphs as communities within these graphs is an increasingly important area of study. Many of the same entities can be found in multiple networks, each representing a different type of relationship. These graphs capturing different relationships between the same entities can be combined into a single graph called a “multi-layered graph”. By finding dense subgraphs containing the same entities within multiple layers of the multi-layered graph, we can increase the confidence these dense subgraphs are communites. This paper has developed an algorithm that takes multi-layered graphs and employs quasi-clique based community discovery for extracting communities. Experimental results on real co-authorship networks show that the proposed approach discover communities that have dense interactions.
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http://hdl.handle.net/10365/23023
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Student Focused, Land Grant, Research Institution

  • Campus Map
    • Campus Map (pdf)
    • Building list
    • Campus Offices
  • Equity
  • Employment
  • Phone/Email Directory
  • Online Services
    • Blackboard
    • One Stop
    • Campus Connection
    • IT Help Desk
    • Libraries
    • Email
    • Student Success Collaborative
  • Registration And Records
    • Course Schedule
    • Dates and Deadlines
North Dakota State University - Libraries
Circulation: (701) 231-8888 | Reference: (701) 231-8886
Administration: (701) 231-8753
Main Library address: 1201 Albrecht Boulevard
Mailing address: Dept #2080 PO Box 6050, Fargo, ND 58108-6050
Site manager: Site manager
Contact Us |