Please use this identifier to cite or link to this item:
https://doi.org/10.1109/TKDE.2006.38
Title: | BORDER: Efficient computation of boundary points | Authors: | Xia, C. Hsu, W. Lee, M.L. Ooi, B.C. |
Keywords: | Boundary points k-nearest neighbor kNN join Reverse k-nearest neighbor |
Issue Date: | 2006 | Citation: | Xia, C., Hsu, W., Lee, M.L., Ooi, B.C. (2006). BORDER: Efficient computation of boundary points. IEEE Transactions on Knowledge and Data Engineering 18 (3) : 289-303. ScholarBank@NUS Repository. https://doi.org/10.1109/TKDE.2006.38 | Abstract: | 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. © 2006 IEEE. | Source Title: | IEEE Transactions on Knowledge and Data Engineering | URI: | http://scholarbank.nus.edu.sg/handle/10635/39278 | ISSN: | 10414347 | DOI: | 10.1109/TKDE.2006.38 |
Appears in Collections: | Staff Publications |
Show full item record
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.