Combining Spatial and Non-spatial Data for Knowledge Discovery: Combined Mining of Spatial and Non-spatial Data - Tapa blanda
Sinopsis
This book is the result of innovative research in combining data from spatial and non-spatial sources for knowledge discovery. Though there has been an explosive growth in data collection and storage capability during the last two decades and many of the data repositories contain location data in the form of spatial references, the wealth of spatial information present in the data is seldom utilised. This unique work establishes that mining of GIS (or other forms of spatial) data in conjunction with the non-spatial data linked together by the location information can successfully detect broad spatial trends over large spatial extents, as well as localised spatial associations. The applicability of the novel framework and algorithmic solutions developed has been demonstrated using real sales data from a supermarket chain. The contents within these covers will be found useful both by data mining students and researchers, and practitioners who would like to use the solution developed for gaining business benefit.
"Sinopsis" puede pertenecer a otra edición de este libro.
Reseña del editor
This book is the result of innovative research in combining data from spatial and non-spatial sources for knowledge discovery. Though there has been an explosive growth in data collection and storage capability during the last two decades and many of the data repositories contain location data in the form of spatial references, the wealth of spatial information present in the data is seldom utilised. This unique work establishes that mining of GIS (or other forms of spatial) data in conjunction with the non-spatial data linked together by the location information can successfully detect broad spatial trends over large spatial extents, as well as localised spatial associations. The applicability of the novel framework and algorithmic solutions developed has been demonstrated using real sales data from a supermarket chain. The contents within these covers will be found useful both by data mining students and researchers, and practitioners who would like to use the solution developed for gaining business benefit.
Biografía del autor
Dr. Shubhamoy Dey is Associate Professor of Information Systems at Indian Institute of Management. He completed his Ph.D from School of Computing, University of Leeds, UK, and Master of Technology from Indian Institute of Technology (IIT-Kgp). He specializes in Data Mining and has 25 years of consulting and teaching experience in UK, USA and India.
"Sobre este título" puede pertenecer a otra edición de este libro.
Resultados de la búsqueda para Combining Spatial and Non-spatial Data for Knowledge...
Imagen del vendedor
Combining Spatial and Non-spatial Data for Knowledge Discovery
Publicado por
LAP LAMBERT Academic Publishing Aug 2011, 2011
ISBN 10: 3845418834
ISBN 13: 9783845418834
Nuevo
Taschenbuch
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is the result of innovative research in combining data from spatial and non-spatial sources for knowledge discovery. Though there has been an explosive growth in data collection and storage capability during the last two decades and many of the data repositories contain location data in the form of spatial references, the wealth of spatial information present in the data is seldom utilised. This unique work establishes that mining of GIS (or other forms of spatial) data in conjunction with the non-spatial data linked together by the location information can successfully detect broad spatial trends over large spatial extents, as well as localised spatial associations. The applicability of the novel framework and algorithmic solutions developed has been demonstrated using real sales data from a supermarket chain. The contents within these covers will be found useful both by data mining students and researchers, and practitioners who would like to use the solution developed for gaining business benefit. 296 pp. Englisch. Nº de ref. del artículo: 9783845418834
Comprar nuevo
EUR 79,00
Envío por EUR 23,00
Se envía de Alemania a Estados Unidos de America
Se envía de Alemania a Estados Unidos de America
Cantidad disponible: 2 disponibles
Imagen del vendedor
Combining Spatial and Non-spatial Data for Knowledge Discovery
Publicado por
LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845418834
ISBN 13: 9783845418834
Nuevo
Tapa blanda
Librería: moluna, Greven, Alemania
Calificación del vendedor: 4 de 5 estrellas
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Dey ShubhamoyDr. Shubhamoy Dey is Associate Professor of Information Systems at Indian Institute of Management. He completed his Ph.D from School of Computing, University of Leeds, UK, and Master of Technology from Indian Institute o. Nº de ref. del artículo: 5481553
Comprar nuevo
EUR 63,42
Envío por EUR 48,99
Se envía de Alemania a Estados Unidos de America
Se envía de Alemania a Estados Unidos de America
Cantidad disponible: Más de 20 disponibles
Imagen del vendedor
Combining Spatial and Non-spatial Data for Knowledge Discovery
Publicado por
LAP LAMBERT Academic Publishing Aug 2011, 2011
ISBN 10: 3845418834
ISBN 13: 9783845418834
Nuevo
Taschenbuch
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is the result of innovative research in combining data from spatial and non-spatial sources for knowledge discovery. Though there has been an explosive growth in data collection and storage capability during the last two decades and many of the data repositories contain location data in the form of spatial references, the wealth of spatial information present in the data is seldom utilised. This unique work establishes that mining of GIS (or other forms of spatial) data in conjunction with the non-spatial data linked together by the location information can successfully detect broad spatial trends over large spatial extents, as well as localised spatial associations. The applicability of the novel framework and algorithmic solutions developed has been demonstrated using real sales data from a supermarket chain. The contents within these covers will be found useful both by data mining students and researchers, and practitioners who would like to use the solution developed for gaining business benefit.Books on Demand GmbH, Überseering 33, 22297 Hamburg 296 pp. Englisch. Nº de ref. del artículo: 9783845418834
Comprar nuevo
EUR 79,00
Envío por EUR 60,00
Se envía de Alemania a Estados Unidos de America
Se envía de Alemania a Estados Unidos de America
Cantidad disponible: 1 disponibles
Imagen del vendedor
Combining Spatial and Non-spatial Data for Knowledge Discovery : Combined Mining of Spatial and Non-spatial Data
Publicado por
LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3845418834
ISBN 13: 9783845418834
Nuevo
Taschenbuch
Librería: AHA-BUCH GmbH, Einbeck, Alemania
Calificación del vendedor: 5 de 5 estrellas
Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book is the result of innovative research in combining data from spatial and non-spatial sources for knowledge discovery. Though there has been an explosive growth in data collection and storage capability during the last two decades and many of the data repositories contain location data in the form of spatial references, the wealth of spatial information present in the data is seldom utilised. This unique work establishes that mining of GIS (or other forms of spatial) data in conjunction with the non-spatial data linked together by the location information can successfully detect broad spatial trends over large spatial extents, as well as localised spatial associations. The applicability of the novel framework and algorithmic solutions developed has been demonstrated using real sales data from a supermarket chain. The contents within these covers will be found useful both by data mining students and researchers, and practitioners who would like to use the solution developed for gaining business benefit. Nº de ref. del artículo: 9783845418834
Comprar nuevo
EUR 79,00
Envío por EUR 62,30
Se envía de Alemania a Estados Unidos de America
Se envía de Alemania a Estados Unidos de America
Cantidad disponible: 1 disponibles