A Three-Stage Consensus-Based Method for Collective Knowledge Determination

  • Dai Tho Dang
  • Van Du Nguyen
  • Ngoc Thanh Nguyen
  • Dosam HwangEmail author
Part of the Studies in Computational Intelligence book series (SCI, volume 769)


Nowadays, the problem of referring knowledge from a large number of autonomous units for solving some problems in the real world has become more and more popular. The need for new techniques to process knowledge in collectives has become urgent because of the rapidly increasing in size of collectives. Many methods for determining the knowledge of collectives have been proposed; however, the traditional data processing methods are inadequate to deal with big collectives. In the present study, we propose a three-stage consensus-based method to determine the knowledge of a big collective. In particular, in the first stage, the sequence partitioning method is applied to partition a big collective into chunks having the same size. Then, the k-means algorithm is used for clustering each chunk into smaller clusters. The knowledge of each chunk is determined based on the knowledge of these clusters. Finally, the knowledge of the big collective is determined based on a set of the knowledge of the chunks. Simulation results have revealed the effectiveness of the proposed method in terms of the running time as well as the quality of the final collective knowledge of a big collective.


Collective knowledge Consensus method Three-stage consensus-based 



This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2017R1A2B4009410).


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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Dai Tho Dang
    • 1
  • Van Du Nguyen
    • 2
  • Ngoc Thanh Nguyen
    • 2
  • Dosam Hwang
    • 1
    Email author
  1. 1.Department of Computer EngineeringYeungnam UniversityGyeongsanRepublic of Korea
  2. 2.Department of Information Systems, Faculty of Computer Science and ManagementWrocław University of Science and TechnologyWrocławPoland

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