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| Visual Sampling Based Clustering Approach VSC |
| Guo Wei; Wang Shi-tong; Chen Ke①; Han Bin |
| School of Information Engineering, Southern Yangtze University, Wuxi 214000, China;①Dept of Computer Science, Nanjing Univ. of Science and Tech., Nanjing 210000, China |
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Abstract Based on the visual sampling principle, the generalized visual sampling based clustering approach VSC is proposed. The clustering approach incorporates the visual sampling principle with the famous Weber law such that it has two distinctive advantages: firstly, it is insensitive to initial conditions; secondly, the reasonable clustering number can be effectively determined by the new Weber-law-based clustering validity index. The experimental results demonstrate its success. Moreover, the link relationship between our approach and algorithm SCA (Similarity-based Clustering Algorithm) recently proposed by Yang Miin-Shen, et al. (2004) is derived. Both theoretic analyses and experimental results show that in many cases, the approach here has almost the same clustering results as algorithm SCA. This fact reveals that the approach can be used to overcome the drawback of SCA, i.e., the parameter γ is very difficult to be well determined.
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Received: 08 July 2004
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2006, Vol. 28 
