The K-Exemplars Clustering Method

Abstract:

In order to apply the concepts of k-means to deal with any specified dissimilarity measures, we propose a k-exemplars clustering method that modifies k-means by restricting the cluster centers on data points. The proposed method not only has similar clustering accuracy as k-means but also faster convergence. According to the definition of the objective function of k-exemplars, the proposed method can be used to deal with a relational data set, and the cluster centers (exemplars) of each cluster will also be extracted. Hence, the k-exemplars can work in an environment with specified dissimilarity measures.

• Periodical: Applied Mechanics and Materials (Volume 376)
• Pages: 224-230
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.376.224
• Online since: August 2013
• Authors: Hsiou Hen Kao, Li Ching Huang, Miin Jye Wen, Kuo Lung Wu
• Keywords: Clustering, K-Exemplars, K-Mean, Relational Data

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