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A Spatial Overlapping Based Similarity Measure Applied to Hierarchical Clustering

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4 Author(s)
Hong Chen ; Sch. of Math. & Comput. Sci., Fujian Normal Univ., Fuzhou ; Gongde Guo ; Yu Huang ; Tianqiang Huang

A novel similarity measure based on spatial overlapping relation is proposed in this paper, which calculates the similarity between a pair of data points by using the mutual overlapping relation between them in a multi-dimensional space. A spatial overlapping based hierarchical clustering method SOHC was also developed and implemented aimed to justify the effectiveness of the proposed similarity measure. SOHC works well both in low-dimensional and high-dimensional datasets, and is able to cluster arbitrary shape of clusters. Moreover, it can work for both numerical and categorical attributes in a uniform way. Experimental results carried out on some public datasets collected from the UCI machine learning repository and predictive toxicology domain show that SOHC is a promising clustering method in data mining.

Published in:

Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on  (Volume:2 )

Date of Conference:

18-20 Oct. 2008