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dc.contributor.authorKörner, Christine
dc.contributor.authorMay, Michael
dc.contributor.authorWrobel, Stefan
dc.date2012-08-01
dc.date.accessioned2018-01-08T09:15:58Z
dc.date.available2018-01-08T09:15:58Z
dc.date.issued2012
dc.identifier.issn1610-1987
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/11301
dc.description.abstractOver the past five to seven years the analysis of trajectory data has established itself as an independent research discipline within the area of data mining. In this article we provide an overview on data characteristics, state-of-the-art preprocessing and analysis methods of trajectory data. We conclude the article with a collection of challenges that arise due to the increasing variety of spatiotemporal data sources and which have to be solved for the application of spatiotemporal analysis methods in practice.
dc.publisherSpringer
dc.relation.ispartofKI - Künstliche Intelligenz: Vol. 26, No. 3
dc.relation.ispartofseriesKI - Künstliche Intelligenz
dc.subjectMobility mining
dc.subjectSpatiotemporal data
dc.titleSpatiotemporal Modeling and Analysis—Introduction and Overview
dc.typeText/Journal Article
mci.reference.pages215-221
gi.identifier.doi10.1007/s13218-012-0215-2


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