A novel clustering algorithm based on the natural reverse nearest neighbor structure

作者：

Highlights：

• The criterion of extracting the core objects is simple and efficient.

• There is no need to set parameters in RNN-NSDC.

• RNN-NSDC can be applied to complex patterns with extremely large variations in density.

• RNN-NSDC is robust to outliers and noises.

摘要

•The criterion of extracting the core objects is simple and efficient.•There is no need to set parameters in RNN-NSDC.•RNN-NSDC can be applied to complex patterns with extremely large variations in density.•RNN-NSDC is robust to outliers and noises.

论文关键词：Clustering,Density core,Natural neighbor,Reverse-nearest neighbor

论文评审过程：Received 3 December 2018, Revised 1 March 2019, Accepted 1 April 2019, Available online 18 April 2019, Version of Record 20 April 2019.

论文官网地址：https://doi.org/10.1016/j.is.2019.04.001