Geographic Data Mining and Knowledge Discovery (eBook, ePUB)

Redaktion: Miller, Harvey J.; Han, Jiawei

• Format: ePub

Produktbeschreibung

This second edition 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.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Erscheinungstermin: 27. Mai 2009
• Englisch
• ISBN-13: 9781040179048
• Artikelnr.: 73346856

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.