Abstract
The essence of human is social relation. In computer, relation can be represented by graph. It may be possible to divide a group of individuals into a few of communities according to the intensity of relation among individuals. The relation between individuals in the same community should be strong, while that between individuals in different communities should be weak. That the intensity of relation between two persons is high means that they trust each other; therefore, strong relation can be used to commit crime, for instance, corruption. Consequently, finding out strong relation can help auditor to reduce difficulty of assuring them of reliability of auditing. Seeing that those algorithms that involve iteration process have fatal defect, the authors of this paper introduce a method used to divide a group into a few of communities based on spectral clustering. This method has the advantage of high speed which means that it has favorable performance when it is used to cope with tremendous amount of data.
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This study was funded by Government Audit Research Foundation of Nanjing Audit University.
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Jibing, H., Hongmei, G., Pengbo, Y. (2019). A Community Discovery Method Based on Spectral Clustering and Its Possible Application in Audit. In: Arai, K., Bhatia, R., Kapoor, S. (eds) Intelligent Computing. CompCom 2019. Advances in Intelligent Systems and Computing, vol 998. Springer, Cham. https://doi.org/10.1007/978-3-030-22868-2_9
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DOI: https://doi.org/10.1007/978-3-030-22868-2_9
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