A General Purpose Platform for Data Clustering Analysis
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Haiyan Qiao
hqiao@csusb.edu
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Brandon Edwards
hqiao@csusb.edu
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Abstract
Grouping objects into meaningful sets - clustering - is an important procedure in many fields of social sciences. Yet, clustering analysis is a difficult problem because many factors come into play in devising a well tuned clustering technique for a given clustering problem. Therefore, an easy-to-use clustering analysis tool is needed. In this paper, we have designed a general purpose clustering analysis platform, which integrates the different clustering algorithms and provides the clustering results in both textual and visual display. This platform will assist the users without any computing or programming background in the selection of appropriate clustering algorithm, improve the quality of clustering, and be extendable to the evaluation of clustering results.
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