An incremental algorithm for clustering spatial data streams: exploring temporal locality
An incremental algorithm for clustering spatial data streams: exploring temporal locality
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Publisher
London: Springer London
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Language
English
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Publisher
London: Springer London
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Scope and Contents
Contents
Clustering sensor data discovers useful information hidden in sensor networks. In sensor networks, a sensor has two types of attributes: a geographic attribute (i.e, its spatial location) and non-geographic attributes (e.g., sensed readings). Sensor data are periodically collected and viewed as spatial data streams, where a spatial data stream cons...
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Full title
An incremental algorithm for clustering spatial data streams: exploring temporal locality
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TN_cdi_proquest_miscellaneous_1464568709
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_miscellaneous_1464568709
Other Identifiers
ISSN
0219-1377
E-ISSN
0219-3116
DOI
10.1007/s10115-013-0636-8
