A fast DBSCAN clustering algorithm by accelerating neighbor searching using Groups method

作者：

Highlights：

• A graph-based index structure is built for speeding up neighbor search operations.

• No additional inputs are required to build the index structure.

• Proposed method is scalable for high-dimensional datasets.

• Handles noise effectively to improve the performance of DBSCAN.

摘要

•A graph-based index structure is built for speeding up neighbor search operations.•No additional inputs are required to build the index structure.•Proposed method is scalable for high-dimensional datasets.•Handles noise effectively to improve the performance of DBSCAN.

论文关键词：Unsupervised learning,Density based clustering,DBSCAN,Neighborhood graph

论文评审过程：Received 30 October 2015, Revised 18 February 2016, Accepted 3 March 2016, Available online 12 March 2016, Version of Record 26 May 2016.

论文官网地址：https://doi.org/10.1016/j.patcog.2016.03.008