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Mining spatio-temporal data

✍ Scribed by Gennady Andrienko; Donato Malerba; Michael May; Maguelonne Teisseire


Book ID
106387377
Publisher
Springer US
Year
2006
Tongue
English
Weight
56 KB
Volume
27
Category
Article
ISSN
0925-9902

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We describe a method for spatio-temporal data mining based on GenSpace graphs. Using familiar calendar and geographical concepts, such as workdays, weeks, climatic regions, and countries, spatio-temporal data can be aggregated into summaries in many ways. We automatically search for a summary with a