Ke-Bing Zhang

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Predictive knowledge discovery is an important knowledge acquisition method. It is also used in the clustering process of data mining. Visualiza-tion is very helpful for high dimensional data analysis, but not precise and this limits its usability in quantitative cluster analysis. In this paper, we adopt a visual technique called HOV 3 to explore and verify(More)
VisPro is a general-purpose visual language generation system, which can produce a wide range of diagrammatic visual programming languages (VPLs) based on Reserved Graph Grammar (RGG), a context sensitive graph grammar. This paper presents an approach to specify the semantic execution sequence of VPLs based on VisPro. In this approach, we use an ordering(More)
This paper presents a visualization approach called Radial Edgeless Tree (RELT) for visualizing and navigating hierarchical information on small screens. Major advantages of the RELT approach include: elegance recursive division of the display area, space-filling, maximum usage of screen estate, and clarity of the hierarchical structure. It offers the(More)
Visualization can be very powerful in revealing cluster structures. However, directly using visualization techniques to verify the validity of clustering results is still a challenge. This is due to the fact that visual representation lacks precision in contrasting clustering results. To remedy this problem, in this paper we propose a novel approach, which(More)
Visualization is helpful for clustering high dimensional data. The goals of visualization in data mining are exploration, confirmation and presentation. However, the most of visual techniques serviced for cluster analysis are focused on cluster presentation rather than cluster exploration. Several techniques are proposed to explore cluster information by(More)