Incremental shared nearest neighbor density-based clustering
Sumeet Singh, Amit C. Awekar · 2013
Shared Nearest Neighbor Density-based clustering (SNN-DBSCAN) is a robust graph-based clustering algorithm and has wide applications from climate data analysis to network intrusion detection. We propose an incremental extension to this algorithm IncSNN-DBSCAN, capable of finding clusters on a dataset to which frequent inserts are made. For each data point, the algorithm maintains four properties: nearest neighbor list, strengths of shared links, total connection strength and topic property. Algorithm only targets points that undergo change to their properties. We prove that, to obtain the exact clustering it is sufficient to re-compute properties for only the targeted points, followed by possible cluster mergers on newly formed links and cluster splits on the deleted links.