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Flickr data for analysing tourists’ spatial behaviour and movement patterns: A comparison of clustering techniques
University of applied sciences Ravensburg-Weingarten.
Institut für Medizinische Informationsverarbeitung Biometrie und Epidemiologie (LMU) Marchioninistr, München, Germany.
Mid Sweden University, Faculty of Human Sciences, Department of Economics, Geography, Law and Tourism. (Etour)ORCID iD: 0000-0003-3964-2716
Mid Sweden University, Faculty of Human Sciences, Department of Economics, Geography, Law and Tourism.ORCID iD: 0000-0002-6610-9303
2020 (English)In: Journal of Hospitality and Tourism Technology, ISSN 1757-9880, E-ISSN 1757-9899Article in journal (Refereed) Epub ahead of print
Abstract [en]

The purpose of this study is to analyse the suitability of photo-sharing platforms, such as Flickr, to extract relevant knowledge on tourists’ spatial movement and point of interest (POI) visitation behaviour and compare the most prominent clustering approaches to identify POIs in various application scenarios.

Place, publisher, year, edition, pages
2020.
Keywords [en]
Big data, Photo sharing, Flickr, Spatial movement patterns, DBSCAN, k-means clustering, Association rules, FP-growth, GSP, Sequential pattern mining
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Other Social Sciences not elsewhere specified
Identifiers
URN: urn:nbn:se:miun:diva-38604DOI: 10.1108/JHTT-08-2017-0059OAI: oai:DiVA.org:miun-38604DiVA, id: diva2:1413059
Available from: 2020-03-09 Created: 2020-03-09 Last updated: 2020-03-13Bibliographically approved

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Fuchs, MatthiasLexhagen, Maria

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Department of Economics, Geography, Law and Tourism
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