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Detecting Communities in Multidimensional Networks based on Network Structural Properties

Khavarinezhad, Nasim | 2014

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  1. Type of Document: M.Sc. Thesis
  2. Language: English
  3. Document No: 47211 (56)
  4. University: Sharif University of Technology, International Campus, Kish Island
  5. Department: Science and Engineering
  6. Advisor(s): Khansari, Mohammad
  7. Abstract:
  8. Complex network studies grow by the scientific community, thanks to the increasing availability of real-world network data. The importance of using analysis on this type of network algorithms and community structure is one of the most important problems in the field of complex networks. Community Detection in a multidimensional network is still under investigation in the research community. The aim of this research is to give an algorithm for community discovery. We have reviewed the basis for multidimensional network analysis and will present a solid repertoire of basic concepts and analytical measures, which take into account the general structure of multidimensional networks. Then, we will propose our algorithm for community discovery with two mechanisms, based on the structural properties of multilayer networks, which are working with a kind of distance matrix and a kind of priority matrix. Finally, we evaluate the algorithm on the real-world multidimensional network to prove the validity, correctness, complexity and speed of our proposed mechanisms in compare to previous works, which can extract communities with complex phenomena in such networks
  9. Keywords:
  10. Network Analysis ; Complex Network ; Community Detection ; Structural Features ; Community Discovery ; Multidimensional Networks ; Label Propagation Algorithm

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