Multilevel Visual Clustering Exploration for Incomplete Time-Series in Water Samples
2018 IEEE Conference on Visual Analytics Science and Technology (VAST)（2018）
Abstract
The VAST 2018 contest provided an opportunity to explore solutions in the pattern identification of 811 incomplete time-series in water samples. In this paper, we present two multilevel approaches (sorted clusters and MCLEAN) to explore and identify trends. Sorted clusters is a combination of clustering with multidimensional scaling to safeguard the similarity in the visualisation of clusters. MCLEAN transforms a multi-dimensional dataset into a network so that it can be investigated at different levels of details.
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Key words
water samples,VAST 2018 contest,pattern identification,sorted clusters,MCLEAN,multilevel visual clustering exploration,incomplete time-series,multidimensional scaling,multidimensional dataset
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