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dc.contributor.authorElmamooz, Golnaz
dc.contributor.authorFinzel, Bettina
dc.contributor.authorNicklas, Daniela
dc.contributor.editorMitschang, Bernhard
dc.contributor.editorNicklas, Daniela
dc.contributor.editorLeymann, Frank
dc.contributor.editorSchöning, Harald
dc.contributor.editorHerschel, Melanie
dc.contributor.editorTeubner, Jens
dc.contributor.editorHärder, Theo
dc.contributor.editorKopp, Oliver
dc.contributor.editorWieland, Matthias
dc.date.accessioned2017-06-21T11:24:37Z
dc.date.available2017-06-21T11:24:37Z
dc.date.issued2017
dc.identifier.isbn978-3-88579-660-2
dc.identifier.issn1617-5468
dc.description.abstractData mining techniques can provide valuable insight to understand mobility in museums. However, the results of such techniques might not be easily understood by the museum staff. In this paper, we propose a graph-based approach to model museum exhibitions, sensor locations, and guiding tasks. We further discuss how route-based trajectory mining can be adapted to work with this graph model and which challenges need to be addressed to cope with the graph dynamics and the continuous flow of sensor data. Based on the demands of two target groups, curators and visitors, three applications are proposed: a museum graph editor, a mobile museum guide, and a curator decision support. We propose an architecture for a platform that provides context information and data mining results to such applications. We claim that our proposed platform can cover many aspects and demands that arise in the museum environment today.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofDatenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-266
dc.subjectmobility in museum
dc.subjectproperty graph model
dc.subjectmuseum knowledge management
dc.subjectincre- mental trajectory data mining
dc.titleTowards Understanding Mobility in Museumsen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages127-136
mci.conference.sessiontitleWorkshop Big (and small) Data in Science and Humanities (BigDS17)
mci.conference.locationStuttgart
mci.conference.date6.-10. März 2017


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