Density peaks clustering algorithm based on natural nearest neighbours and its application in network advertising recognition
by Zhanfeng Yao; Tanghuai Fan; Xin Li; Jia Zhao
International Journal of Wireless and Mobile Computing (IJWMC), Vol. 18, No. 3, 2020

Abstract: For the density peaks clustering algorithm, when dealing with multi-scale and manifold datasets, the algorithm cannot find the correct density peaks, and the distribution strategy is prone to the cascading effect of distribution errors. Hence, we propose a density peaks clustering algorithm based on natural nearest neighbours. In the proposed algorithm, the natural nearest neighbours of the sample are taken as the initial density by Gauss summation, and then it compares this initial density with the initial density of its k-nearest neighbours to form the final local density, the natural nearest neighbour information used to strengthen the relationship between samples, redefine the similarity measure between samples, and use it for remaining sample allocation. The experimental results on the synthetic datasets and network advertising recognition dataset show that the clustering effect of the proposed algorithm is better than that of DPC, DPCSA and FNDPCs, and more accurate advertising screening effect is achieved.

Online publication date: Mon, 20-Apr-2020

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