Leveraging Block-Diagonal Structure for Robust and Efficient High-Dimensional Clustering
The core message of this paper is to introduce an improved version of DBSCAN, called Block-Diagonal guided DBSCAN (BD-DBSCAN), that leverages the block-diagonal property of the similarity graph to guide the clustering procedure and overcome the limitations of DBSCAN in handling high-dimensional large-scale data.