BRIM: an efficient boundary points detecting algorithm

Authors:
Bao-Zhi Qiu;Feng Yue;Jun-Yi Shen
Affiliations:
School of Information & Engineering, Zhengzhou University, Zhengzhou, China;School of Information & Engineering, Zhengzhou University, Zhengzhou, China;School of Electronic Information & Engineering, Xi'an Jiaotong University, Xi'an, China
Venue:
PAKDD'07 Proceedings of the 11th Pacific-Asia conference on Advances in knowledge discovery and data mining
Year:
2007

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Abstract

In order to detect boundary points of clusters effectively, we propose a technique making use of a point's distribution feature of its Eps neighborhood to detect boundary points, and develop a boundary points detecting algorithm BRIM (an efficient Boundary points detecting algorithm). Experimental results show that BRIM can detect boundary points in noisy datasets containing clusters of different shapes and sizes effectively and efficiently.