Geographic Data Mining and Knowledge Discovery (eBook, PDF)

Redaktion: Miller, Harvey J.; Han, Jiawei

• Format: PDF

Produktbeschreibung

The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and Spatiotemporal DatabasesSince 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 EditionUpdated material on geographic knowledge discovery (GKD), GDW research, map cubes, spatial dependency, spatial clustering methods, clustering techniques for trajectory data, the INGENS 2.0 software, and GVis techniquesNew chapter on data quality issues in GKDNew chapter that presents a tree-based partition querying methodology for medoid computation in large spatial databasesNew chapter that discusses the use of geographically weighted regression as an exploratory techniqueNew chapter that gives an integrated approach to multivariate analysis and geovisualizationFive new chapters on knowledge discovery from spatiotemporal and mobile objects databasesGeographic 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.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 486
• Erscheinungstermin: 27. Mai 2009
• Englisch
• ISBN-13: 9781420073980
• Artikelnr.: 42619513

Autorenporträt

Jiawei Han, Harvey J. Miller

Inhaltsangabe

Introduction. Spatiotemporal Data Mining Paradigms and Methodologies.
Fundamentals of Spatial Data Warehousing for Geographic Knowledge
Discovery. Analysis of Spatial Data with Map Cubes: Highway Traffic Data.
Data Quality Issues and Geographic Knowledge Discovery. Spatial
Classification and Prediction Models for Geospatial Data Mining. An
Overview of Clustering Methods in Geographic Data Analysis. Computing
Medoids in Large Spatial Datasets. Looking for a Relationship? Try GWR.
Leveraging the Power of Spatial Data Mining to Enhance the Applicability of
GIS Technology. Visual Exploration and Explanation in Geography: Analysis
with Light. Multivariate Spatial Clustering and Geovisualization. Toward
Knowledge Discovery about Geographic Dynamics in Spatiotemporal Databases.
The Role of a Multitier Ontological Framework in Reasoning to Discover
Meaningful Patterns of Sustainable Mobility. Periodic Pattern Discovery
from Trajectories of Moving Objects. Decentralized Spatial Data Mining for
Geosensor Networks. Beyond Exploratory Visualization of Space-Time Paths.