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Abstract: The clustering problem has been widely studied since it arises in many application domains in engineering, business and social science. It aims at identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity clusters. Traditional clustering algorithms use distance functions to measure similarity and are not suitable for high dimensional spaces. In this paper, we propose a non-distance based clustering algorithm for high... (Update)
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BibTeX entry: (Update)
Shenghuo Zhu and Tao Li. An algorithm for non-distance based clustering in high dimensional spaces. Technical Report 763, University of Rochester, Computer Science Department, Rochester, NY, 2002. http://citeseer.ist.psu.edu/zhu02algorithm.html More
@techreport{ zhu02algorithm,
author = "Shenghuo Zhu and Tao Li",
title = "An Algorithm for Non-Distance Based Clustering in High Dimensional Spaces",
number = "TR763",
year = "2002",
url = "citeseer.ist.psu.edu/zhu02algorithm.html" }
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