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BORDER: efficient computation of boundary points

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4 Author(s)
Chenyi Xia ; Sch. of Comput., Nat. Univ. of Singapore, Singapore ; Hsu, W. ; Mong Li Lee ; Beng Chin Ooi

This work addresses the problem of finding boundary points in multidimensional data sets. Boundary points are data points that are located at the margin of densely distributed data such as a cluster. We describe a novel approach called BORDER (a BOundaRy points DEtectoR) to detect such points. BORDER employs the state-of-the-art database technique - the Gorder kNN join and makes use of the special property of the reverse k nearest neighbor (RkNN). Experimental studies on data sets with varying characteristics indicate that BORDER is able to detect the boundary points effectively and efficiently.

Published in:

Knowledge and Data Engineering, IEEE Transactions on  (Volume:18 ,  Issue: 3 )