Parallel Co-location Pattern Mining in Cloud for GIS Application - Refaye, Eman
36,99 €
inkl. MwSt.
Versandkostenfrei*
Versandfertig in 1-2 Wochen
payback
18 °P sammeln
  • Broschiertes Buch

Spatial data mining become one of the important areas because of the rapid evolution in technology which leads in big spatial data. Co-locations pattern mining is an interesting and important issue in spatial data mining area which discovers the subsets of features whose events are frequently located together in geographic space. Spatial proximity is the important concept to determine the Col-ocation patterns from massive data. The computation of co-location pattern discovery is very expensive with big data volume and nearby existence of neighborhoods. So there is number of spatial co-location…mehr

Andere Kunden interessierten sich auch für
Produktbeschreibung
Spatial data mining become one of the important areas because of the rapid evolution in technology which leads in big spatial data. Co-locations pattern mining is an interesting and important issue in spatial data mining area which discovers the subsets of features whose events are frequently located together in geographic space. Spatial proximity is the important concept to determine the Col-ocation patterns from massive data. The computation of co-location pattern discovery is very expensive with big data volume and nearby existence of neighborhoods. So there is number of spatial co-location mining algorithms have been developed to overcome these drawbacks.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Autorenporträt
Eman Refaye, Master of Science Degree in Information Systems, Faculty of Computers & Information - Cairo University. GIS specialist, Assistant Lecture in Cairo Institute for Computer Science - Cairo, Egypt.