Abstract
As we know, determining the knowledge of a collective is an important task. However, there exists another important issue with its quality. The quality reflects how good the collective knowledge is. It is useful in some cases such as: to add or remove some knowledge members to improve quality of collective knowledge or evaluate whether collective knowledge is good enough or not. In this paper, we consider consistency functions that proposed by taking into account both density and coherence factors. Then we analyze influence of their values on the quality of collective knowledge using binary vector structure. The experiments showed that both density and coherence have a significant influence on the quality of collective knowledge.
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Gębala, M., Nguyen, V.D., Nguyen, N.T. (2015). An Analysis of Influence of Consistency Degree on Quality of Collective Knowledge Using Binary Vector Structure. In: Camacho, D., Kim, SW., Trawiński, B. (eds) New Trends in Computational Collective Intelligence. Studies in Computational Intelligence, vol 572. Springer, Cham. https://doi.org/10.1007/978-3-319-10774-5_1
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DOI: https://doi.org/10.1007/978-3-319-10774-5_1
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10773-8
Online ISBN: 978-3-319-10774-5
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