Limiting the Neighborhood: De-Small-World Network for Outbreak Prevention

  • Ruoming Jin
  • Yelong Sheng
  • Lin Liu
  • Xue-Wen Chen
  • NhatHai PhanEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11917)


In this work, we study a basic and practically important strategy to help prevent and/or delay an outbreak in the context of network: limiting the contact between individuals. In this paper, we introduce the average neighborhood size as a new measure for the degree of being small-world and utilize it to formally define the de-small-world network problem. We also prove the NP-hardness of the general reachable pair cut problem and propose a greedy edge betweenness based approach as the benchmark in selecting the candidate edges for solving our problem. Furthermore, we transform the de-small-world network problem as an OR-AND Boolean function maximization problem, which is also an NP-hardness problem. In addition, we develop a numerical relaxation approach to solve the Boolean function maximization and the de-small-world problem. Also, we introduce the short-betweenness, which measures the edge importance in terms of all short paths with distance no greater than a certain threshold, and utilize it to speed up our numerical relaxation approach. The experimental evaluation demonstrates the effectiveness and efficiency of our approaches.


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Ruoming Jin
    • 1
  • Yelong Sheng
    • 1
  • Lin Liu
    • 1
  • Xue-Wen Chen
    • 2
  • NhatHai Phan
    • 3
    Email author
  1. 1.Department of Computer ScienceKent State UniversityKentUSA
  2. 2.Department of EECSThe University of KansasLawrenceUSA
  3. 3.College of ComputingNew Jersey Institute of TechnologyNewarkUSA

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