Geographic Data Mining and Knowledge Discovery
CRC Press (Verlag)
978-1-138-58266-8 (ISBN)
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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
Updated 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 techniques
New chapter on data quality issues in GKD
New chapter that presents a tree-based partition querying methodology for medoid computation in large spatial databases
New chapter that discusses the use of geographically weighted regression as an exploratory technique
New chapter that gives an integrated approach to multivariate analysis and geovisualization
Five new chapters on knowledge discovery from spatiotemporal and mobile objects databases
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.
Introduction
Harvey J. Miller and Jiawei Han
Spatiotemporal Data Mining Paradigms and Methodologies
John F. Roddick and Brian G. Lees
Fundamentals of Spatial Data Warehousing for Geographic Knowledge Discovery
Yvan Bédard and Jiawei Han
Analysis of Spatial Data with Map Cubes: Highway Traffic Data
Chang-Tien Lu, Arnold P. Boedihardjo, and Shashi Shekhar
NEW! Data Quality Issues and Geographic Knowledge Discovery
Marc Gervais, Yvan Bedard, Marie-Andree Levesque, Eveline Bernier, and Rodolphe Devillers
Spatial Classification and Prediction Models for Geospatial Data Mining
Shashi Shekhar, Ranga Raju Vatsavai, and Sanjay Chawla
An Overview of Clustering Methods in Geographic Data Analysis
Jiawei Han, Jae-Gil Lee, and Micheline Kamber
NEW! Computing Medoids in Large Spatial Datasets
Kyriakos Mouratidis, Dimitris Papadias, Spiros Papadimitriou
NEW! Looking for a Relationship? Try GWR
A. Stewart Fotheringham, Martin Charlton, and Urška Demšar
Leveraging the Power of Spatial Data Mining to Enhance the Applicability of GIS Technology
Donato Malerba, Antonietta Lanza, and Annalisa Appice
Visual Exploration and Explanation in Geography: Analysis with Light
Mark Gahegan
NEW! Multivariate Spatial Clustering and Geovisualization
Diansheng Guo
NEW! Toward Knowledge Discovery about Geographic Dynamics in Spatiotemporal Databases}
May Yuan
NEW! The Role of a Multitier Ontological Framework in Reasoning to Discover Meaningful Patterns of Sustainable Mobility
Monica Wachowicz, Jose Macedo, Chiara Renso, and Arend Ligtenberg
NEW! Periodic Pattern Discovery from Trajectories of Moving Objects
Huiping Cao, Nikos Mamoulis, and David W. Cheung
NEW! Decentralized Spatial Data Mining for Geosensor Networks
Patrick Laube and Matt Duckham
NEW! Beyond Exploratory Visualization of Space-Time Paths
Menno-Jan Kraak and Otto Huisman
Erscheint lt. Verlag | 31.12.2023 |
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Reihe/Serie | Chapman & Hall/CRC Data Mining and Knowledge Discovery Series |
Zusatzinfo | 162 Illustrations, black and white |
Verlagsort | London |
Sprache | englisch |
Maße | 156 x 234 mm |
Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
Naturwissenschaften ► Geowissenschaften ► Geografie / Kartografie | |
Weitere Fachgebiete ► Land- / Forstwirtschaft / Fischerei | |
ISBN-10 | 1-138-58266-2 / 1138582662 |
ISBN-13 | 978-1-138-58266-8 / 9781138582668 |
Zustand | Neuware |
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