A novel density-based clustering algorithm using nearest neighbor graph

作者：

Highlights：

• Nearest neighbor graph can indicate the samples that lying within the local dense regions of dataset without any input parameter.

• A clustering algorithm named ADBSCAN is developed based on the nearest neighbor graph properties.

• Experiments on different types of datasets demonstrate the superior performance and the robust to parameters of ADBSCAN.

摘要

•Nearest neighbor graph can indicate the samples that lying within the local dense regions of dataset without any input parameter.•A clustering algorithm named ADBSCAN is developed based on the nearest neighbor graph properties.•Experiments on different types of datasets demonstrate the superior performance and the robust to parameters of ADBSCAN.

论文关键词：Density-based clustering,Nearest neighbor graph,DBSCAN

论文评审过程：Received 30 October 2018, Revised 28 November 2019, Accepted 15 January 2020, Available online 17 January 2020, Version of Record 30 January 2020.

论文官网地址：https://doi.org/10.1016/j.patcog.2020.107206