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An Improvement of the Two-Stage Consensus-Based Approach for Determining the Knowledge of a Collective

  • Van Du NguyenEmail author
  • Ngoc Thanh Nguyen
  • Dosam Hwang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9875)

Abstract

Generally the knowledge of a collective, which is considered as a representative of the knowledge states in a collective, is often determined based on a single-stage approach. For big data, however, a collective is often very large, a multi-stage approach can be used. In this paper we present an improvement of the two-stage consensus-based approach for determining the knowledge of a large collective. For this aim, clustering methods are used to classify a large collective into smaller ones. The first stage of consensus choice aims at determining the representatives of these smaller collectives. Then these representatives will be treated as the knowledge states of a new collective which will be the subject for the second stage of consensus choice. In addition, all the collectives will be checked for susceptibility to consensus in both stages of consensus choice process. Through experiments analysis, the improvement method is useful in minimizing the difference between single-stage and two-stage consensus choice approaches in determining the knowledge of a large collective.

Keywords

Collective knowledge Inconsistency knowledge Two-stage consensus choice 

Notes

Acknowledgement

We would like to thank Gideon Rosenblatt, Quoc Trung Bui, Erik Steiner for sharing datasets.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

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

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