An efficient and effective algorithm for density biased sampling Alexandros Nanopoulos, Yannis Manolopoulos, and Yannis Theodoridis   View Paper (PDF)   Return to Spatial search and moving objects Abstract In this paper we describe a new density-biased sampling algorithm. It exploits spatial indexes and the local density information they preserve, to provide improved quality of sampling result and fast access to elements of the dataset. It attains improved sampling quality, with respect to factors like skew, noise or dimensionality. Moreover, it has the advantage of efficiently handling dynamic updates, and it requires low execution times. The performance of the proposed method is examined experimentally. The comparative results illustrate its superiority over existing methods. DiSC'03 © 2003 Association for Computing Machinery