Geographic Data Mining and Knowledge Discovery Contributor(s): Miller, Harvey J. (Editor), Han, Jiawei (Editor) |
|
ISBN: 1420073974 ISBN-13: 9781420073973 Publisher: CRC Press OUR PRICE: $161.50 Product Type: Hardcover - Other Formats Published: May 2009 Annotation: This second edition reflects the current state of the art in the field. It includes updated material on geographic knowledge discovery, geographic data warehouse research, map cubes, spatial dependency, spatial clustering methods, clustering techniques for trajectory data, INGENS 2.0, and geovisualization techniques. Recognizing the growth in mobile technologies and trajectory data, this edition provides five new chapters on knowledge discovery from spatiotemporal and mobile objects databases. It also contains new chapters on data quality issues, medoid computation, geographically weighted regression, and an integrated approach to multivariate analysis and geovisualization. |
Additional Information |
BISAC Categories: - Computers | Databases - Data Mining - Travel - Computers | Programming - Games |
Dewey: 910.285 |
LCCN: 2009010969 |
Physical Information: 1.1" H x 6.3" W x 9.3" (1.80 lbs) 486 pages |
Descriptions, Reviews, Etc. |
Publisher Description: The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and Spatiotemporal Databases Since the publication of the first edition of Geographic Data Mining and Knowledge Discovery, new techniques for geographic data warehousing (GDW), spatial data mining, and geovisualization (GVis) have been developed. In addition, there has been a rise in the use of knowledge discovery techniques due to the increasing collection and storage of data on spatiotemporal processes and mobile objects. Incorporating these novel developments, this second edition reflects the current state of the art in the field. New to the Second Edition
Geographic data mining and knowledge discovery is a promising young discipline with many challenging research problems. This book shows that this area represents an important direction in the development of a new generation of spatial analysis tools for data-rich environments. Exploring various problems and possible solutions, it will motivate researchers to develop new methods and applications in this emerging field. |