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http://hdl.handle.net/1942/34299| Title: | Multilevel Visual Clustering Exploration for Incomplete Time-Series in Water Samples | Authors: | Alcaide, Daniel AERTS, Jan |
Issue Date: | 2018 | Publisher: | IEEE | Source: | 2018 IEEE CONFERENCE ON VISUAL ANALYTICS SCIENCE AND TECHNOLOGY (VAST), IEEE, p. 116 -117 | 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. | Document URI: | http://hdl.handle.net/1942/34299 | ISBN: | 9781538668610 | DOI: | 10.1109/VAST.2018.8802480 | ISI #: | WOS:000502616800022 | Category: | C1 | Type: | Proceedings Paper |
| Appears in Collections: | Research publications |
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