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Local distribution search is used in query-driven visualization for identifying salient features. Due to the high computational and storage costs, local distribution search in multi-field datasets is challenging. In this paper, we introduce two high performance, memory efficient algorithms for searching for local distributions that are characterized by marginal and joint features in multi-field datasets...
Correlation analysis is one of the most important tasks in the field of visualization research and data mining. This paper proposes a novel dissimilarity-preserving cluster algorithm that characterizes not only the time-varying patterns but also the spatial positions to summary the correlation connection in multi-variable and time-varying data sets. A temporal multi-variable structure is defined to...
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