Mining and clustering mobility evolution patterns from social media for urban informatics
Mining and clustering mobility evolution patterns from social media for urban informatics
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London: Springer London
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English
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Publisher
London: Springer London
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In this paper, given a set of check-in data, we aim at discovering representative daily movement behavior of users in a city. For example, daily movement behavior on a weekday may show users moving from one to another spatial region associated with time information. Since check-in data contain both spatial and temporal information, we propose a mob...
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Mining and clustering mobility evolution patterns from social media for urban informatics
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TN_cdi_proquest_miscellaneous_1800498042
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_1800498042
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ISSN
0219-1377
E-ISSN
0219-3116
DOI
10.1007/s10115-015-0853-4
