Spatio-temporal clustering (Contributo in volume (capitolo o saggio))

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Label
  • Spatio-temporal clustering (Contributo in volume (capitolo o saggio)) (literal)
Anno
  • 2010-01-01T00:00:00+01:00 (literal)
Alternative label
  • Kisilevich S.; Mansmann F.; Nanni M.; Rinzivillo S. (2010)
    Spatio-temporal clustering
    Springer, New York, USA, 2010
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Kisilevich S.; Mansmann F.; Nanni M.; Rinzivillo S. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#citta
  • New York, USA (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
  • In: Data Mining and Knowledge Discovery Handbook. vol. 6 pp. 855 - 874. Oded Maimon, Lior Rokach. (Springer Science+Business Media). New York, USA: Springer, 2010. (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#descrizioneSinteticaDelProdotto
  • Spatio-temporal clustering is a process of grouping objects based on their spatial and temporal similarity. It is relatively new subfield of data mining which gained high popularity especially in geographic information sciences due to the pervasiveness of all kinds of location-based or environmental devices that record position, time or/and environmental properties of an object or set of objects in real-time. As a consequence, different types and large amounts of spatio-temporal data became available that introduce new challenges to data analysis and require novel approaches to knowledge discovery. In this chapter we concentrate on the spatio-temporal clustering in geographic space. First, we provide a classification of different types of spatio-temporal data. Then, we focus on one type of spatio-temporal clustering - trajectory clustering, provide an overview of the state-of-the-art approaches and methods of spatio-temporal clustering and finally present several scenarios in different (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • University of Konstanz, Germany, CNR-ISTI, Pisa (literal)
Titolo
  • Spatio-temporal clustering (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#inCollana
  • Data Mining and Knowledge Discovery Handbook (literal)
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