Geographic Data Mining and Knowledge Discovery, Second Edition
Geographic Data Mining and Knowledge Discovery, Second Edition by Harvey J. Miller, published by Taylor & Francis on May 27, 2009, spans 486 pages and is presented in English. This edition builds upon the foundational concepts introduced in the first edition, reflecting advancements in geographic data warehousing, spatial data mining, and geovisualization. It addresses the evolving landscape of knowledge discovery techniques, particularly in light of the growing volume of data related to spatiotemporal processes and mobile objects.
Readers will find updated discussions on geographic knowledge discovery, including new chapters that delve into data quality issues, tree-based partition querying methodologies, and the application of geographically weighted regression. The book also introduces innovative techniques for spatial clustering and provides insights into knowledge discovery from spatiotemporal and mobile object databases. This comprehensive resource aims to inspire researchers to explore new methods and applications within this dynamic field, emphasizing the importance of developing advanced spatial analysis tools for data-rich environments.
Official synopsis Publisher
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
- 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.
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