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Geographic Data Mining And Knowledge Discovery 2nd Edition 2009 at Meripustak

Geographic Data Mining And Knowledge Discovery 2nd Edition 2009 by Miller Harvey J. Et.Al, Taylor & Francis

Books from same Author: Miller Harvey J. Et.Al

Books from same Publisher: Taylor & Francis

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  • General Information  
    Author(s)Miller Harvey J. Et.Al
    PublisherTaylor & Francis
    ISBN9781138582668
    Pages486
    BindingHardback
    LanguageEnglish
    Publish YearMay 2009

    Description

    Taylor & Francis Geographic Data Mining And Knowledge Discovery 2nd Edition 2009 by Miller Harvey J. Et.Al

    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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