LFPeers: Temporal Similarity Search in Covid-19 Data

dc.contributor.authorBurmeister, Janen_US
dc.contributor.authorBernard, Jürgenen_US
dc.contributor.authorKohlhammer, Jörnen_US
dc.contributor.editorVrotsou, Katerina and Bernard, Jürgenen_US
dc.date.accessioned2021-06-12T11:22:15Z
dc.date.available2021-06-12T11:22:15Z
dc.date.issued2021
dc.description.abstractWhile there is a wide variety of visualizations and dashboards to help understand the data of the Covid-19 pandemic, hardly any of these support important analytical tasks, especially of temporal attributes. In this paper, we introduce a general concept for the analysis of temporal and multimodal data and the system LFPeers that applies this concept to the analysis of countries in a Covid-19 dataset. Our concept divides the analysis in two phases: a search phase to find the most similar objects to a target object before a time point t0, and an exploration phase to analyze this subset of objects after t0. LFPeers targets epidemiologists and the public who want to learn from the Covid-19 pandemic and distinguish successful and ineffective measures.en_US
dc.description.sectionheadersTemporal Data and Clustering
dc.description.seriesinformationEuroVis Workshop on Visual Analytics (EuroVA)
dc.identifier.doi10.2312/eurova.20211098
dc.identifier.isbn978-3-03868-150-2
dc.identifier.pages49-53
dc.identifier.urihttps://doi.org/10.2312/eurova.20211098
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurova20211098
dc.publisherThe Eurographics Associationen_US
dc.titleLFPeers: Temporal Similarity Search in Covid-19 Dataen_US
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