Stream Clustering Based on Kernel Density Estimation

Authors:
Stefano Lodi;Gianluca Moro;Claudio Sartori
Affiliations:
Department of Electronics, Computer Science and Systems, University of Bologna, Viale Risorgimento 2, IT-40136 Bologna BO, Italy, email: {stefano.lodi,gianluca.moro,claudio.sartori}@unibo.it;Department of Electronics, Computer Science and Systems, University of Bologna, Viale Risorgimento 2, IT-40136 Bologna BO, Italy, email: {stefano.lodi,gianluca.moro,claudio.sartori}@unibo.it;Department of Electronics, Computer Science and Systems, University of Bologna, Viale Risorgimento 2, IT-40136 Bologna BO, Italy, email: {stefano.lodi,gianluca.moro,claudio.sartori}@unibo.it
Venue:
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Year:
2006

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Abstract

We present a novel algorithm for clustering streams of multidimensional points based on kernel density estimates of the data. The algorithm requires only one pass over each data point and a constant amount of space, which depends only on the accuracy of clustering. The algorithm recognizes clusters of nonspherical shapes and handles both inserted and deleted objects in the input stream. Querying the membership of a point in a cluster can be answered in constant time.