DBSCAN Revisited 论文

摘要

DBSCAN is a popular method for clustering multi-dimensional objects. Just as notable as the method's vast success is the research community's quest for its efficient computation. The original KDD'96 paper claimed an algorithm with O(n log n) running time, where n is the number of objects. Unfortunately, this is a mis-claim; and that algorithm actually requires O(n2) time. There has been a fix in 2D space, where a genuine O(n log n)-time algorithm has been found. Looking for a fix for dimensionality d ≥ 3 is currently an important open problem.