Verlag: LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3846592153 ISBN 13: 9783846592151
Sprache: Englisch
Anbieter: Buchpark, Trebbin, Deutschland
Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 116 | Sprache: Englisch | Produktart: Bücher.
Verlag: LAP LAMBERT Academic Publishing Nov 2011, 2011
ISBN 10: 3846592153 ISBN 13: 9783846592151
Sprache: Englisch
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
EUR 49,00
Währung umrechnenAnzahl: 2 verfügbar
In den WarenkorbTaschenbuch. Zustand: Neu. Neuware -The explosive growth of spatial data and the widespread use of spatial databases put emphasis on the extraction of interesting and implicit knowledge such as the spatial pattern or other significant mode not explicitly stored in the spatial databases. Knowledge discovery in large spatial database is important for the extraction of implicit knowledge. Spatial relations or other patterns are not explicitly stored in spatial database. Traditional Data mining techniques are not efficient and effective to mine the spatial data due to its unique features such as spatial dependency, heterogeneity, spatially aggregated data etc. Thus, new and efficient mining methods are needed to discover knowledge from large spatial databases. A descriptive modeling technique for georeferenced data is discussed and it is also used to solve the regionalization problem. Multi Level Multi Dimensional is an important aspect for Spatial Data. The Multi Level Multi Dimensional pattern discovery on spatial data is presented here. Mining the trajectory data or mobility data is an emerging area of research. The Trajectory data classifier which is based on the Nearest Neighbor is introduced.Books on Demand GmbH, Überseering 33, 22297 Hamburg 116 pp. Englisch.
Verlag: LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3846592153 ISBN 13: 9783846592151
Sprache: Englisch
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 102,24
Währung umrechnenAnzahl: 1 verfügbar
In den WarenkorbPaperback. Zustand: Brand New. 116 pages. 8.58x5.83x0.31 inches. In Stock.