Grid-based DBSCAN: Indexing and inference

作者：

Highlights：

• The proposed method extends grid-based DBSCAN scalable to higher-dimensional dataset.

• Cluster forest is devised to alleviate redundancies in the merging step.

• HyperGrid Bitmap is used to index non-empty grids for efficient neighbor grid queries.

• Experiments show performance superiority of proposed method on real/synthetic data.

摘要

•The proposed method extends grid-based DBSCAN scalable to higher-dimensional dataset.•Cluster forest is devised to alleviate redundancies in the merging step.•HyperGrid Bitmap is used to index non-empty grids for efficient neighbor grid queries.•Experiments show performance superiority of proposed method on real/synthetic data.

论文关键词：Density-based clustering,Grid-based DBSCAN,Union-find algorithm

论文评审过程：Received 26 April 2018, Revised 3 December 2018, Accepted 24 January 2019, Available online 28 January 2019, Version of Record 5 February 2019.

论文官网地址：https://doi.org/10.1016/j.patcog.2019.01.034