Dynamic Density Based Clustering
Junhao Gan, Yufei Tao · 2017
Dynamic clustering---how to efficiently maintain data clusters along with updates in the underlying dataset---is a difficult topic. This is especially true for density-based clustering, where objects are aggregated based on transitivity of proximity, under which deciding the cluster(s) of an object may require the inspection of numerous other objects. The phenomenon is unfortunate, given the popular usage of this clustering approach in many applications demanding data updates.