Descriptive Modelling and Pattern Discovery in Spatial Data Mining

Name: Descriptive Modelling and Pattern Discovery in Spatial Data Mining
Brand: LAP Lambert Academic Publishing
SKU: 9783846592151
Price: 236.02 RON
Availability: InStock

Regionalisation and Association Rule Mining

Autor: Lokesh Kumar Sharma

Limbă:

Legare: Carte broșată

Editura: LAP Lambert Academic Publishing

Disponibilitate: În depozitul extern

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The explosive growth of spatial data and the widespread use of spatial databases put emphasis on the...

Informații despre carte

Autor

Lokesh Kumar Sharma

Limbă

engleză

Legare

Carte - Carte broșată

Publicat

2011

Pagini

116

EAN

9783846592151

Enbook ID

07089574

Editura

LAP Lambert Academic Publishing

Greutate

177

Dimensiuni

149 x 219 x 7

Descriere completă

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.

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Descriptive Modelling and Pattern Discovery in Spatial Data Mining

Regionalisation and Association Rule Mining

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