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Revealing Underlying Structure and Behaviour from Movement Data

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dc.contributor.authorSester, Monika
dc.contributor.authorFeuerhake, Udo
dc.contributor.authorKuntzsch, Colin
dc.contributor.authorZhang, Lijuan
dc.date.accessioned2018-01-08T09:15:59Z
dc.date.available2018-01-08T09:15:59Z
dc.date.issued2012
dc.description.abstractSpatio-temporal trajectories contain implicit knowledge about the movement of individuals, which is relevant for problems in various domains, e.g. animal migration, traffic analysis, security. In this paper we present real-time approaches to segment trajectories into meaningful parts which reflect the underlying typical behaviour or structure. Based on this information atypical behaviour can be identified.
dc.identifier.pissn1610-1987
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/11302
dc.publisherSpringer
dc.relation.ispartofKI - Künstliche Intelligenz: Vol. 26, No. 3
dc.relation.ispartofseriesKI - Künstliche Intelligenz
dc.subjectOn-line structure recognition
dc.subjectSpatio-temporal data analysis
dc.titleRevealing Underlying Structure and Behaviour from Movement Data
dc.typeText/Journal Article
gi.citation.endPage231
gi.citation.startPage223

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Künstliche Intelligenz 26(3) - August 2012