Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/34299
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dc.contributor.authorAlcaide, Daniel-
dc.contributor.authorAERTS, Jan-
dc.date.accessioned2021-06-21T08:02:06Z-
dc.date.available2021-06-21T08:02:06Z-
dc.date.issued2018-
dc.date.submitted2021-03-29T08:38:23Z-
dc.identifier.citation2018 IEEE CONFERENCE ON VISUAL ANALYTICS SCIENCE AND TECHNOLOGY (VAST), IEEE, p. 116 -117-
dc.identifier.isbn9781538668610-
dc.identifier.issn2325-9442-
dc.identifier.urihttp://hdl.handle.net/1942/34299-
dc.description.abstractThe 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.-
dc.language.isoen-
dc.publisherIEEE-
dc.titleMultilevel Visual Clustering Exploration for Incomplete Time-Series in Water Samples-
dc.typeProceedings Paper-
local.bibliographicCitation.conferencedateOctober 21-26, 2018-
local.bibliographicCitation.conferencename13th IEEE Conference on Visual Analytics Science and Technology (VAST)-
local.bibliographicCitation.conferenceplaceBerlin, Germany-
dc.identifier.epage117-
dc.identifier.spage116-
local.bibliographicCitation.jcatC1-
local.publisher.place345 E 47TH ST, NEW YORK, NY 10017 USA-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
dc.identifier.doi10.1109/VAST.2018.8802480-
dc.identifier.isiWOS:000502616800022-
local.provider.typeCrossRef-
local.bibliographicCitation.btitle2018 IEEE CONFERENCE ON VISUAL ANALYTICS SCIENCE AND TECHNOLOGY (VAST)-
local.uhasselt.uhpubno-
item.contributorAlcaide, Daniel-
item.contributorAERTS, Jan-
item.fullcitationAlcaide, Daniel & AERTS, Jan (2018) Multilevel Visual Clustering Exploration for Incomplete Time-Series in Water Samples. In: 2018 IEEE CONFERENCE ON VISUAL ANALYTICS SCIENCE AND TECHNOLOGY (VAST), IEEE, p. 116 -117.-
item.accessRightsClosed Access-
item.fulltextNo Fulltext-
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