Geographic Data Mining and Knowledge Discovery 1st Edition by Harvey Miller ISBN 1558604898 9781558604896
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Product details:
ISBN 10: 1558604898
ISBN 13: 9781558604896
Author: Harvey J. Miller
Here’s the resource you need if you want to apply today’s most powerful data mining techniques to meet real business challenges. Data Mining: Concepts and Techniques equips you with a sound understanding of data mining principles and teaches you proven methods for knowledge discovery in large corporate databases.
Written expressly for database practitioners and professionals, this book begins with a conceptual introduction designed to get you up to speed. This is followed by a comprehensive and state-of-the-art coverage of data mining concepts and techniques. Each chapter functions as a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. Wherever possible, the authors raise and answer questions of utility, feasibility, optimization, and scalability, keeping your eye on the issues that will affect your project’s results and your overall success.
Data Mining: Concepts and Techniques is the master reference that practitioners and researchers have long been seeking. It is also the obvious choice for academic and professional classrooms.
Classroom Features Available Online:
– instructor’s manual
– course slides (in PowerPoint)
– course supplementary readings
– sample assignments and course projects
* Offers a comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business data.
* Organized as a series of stand-alone chapters so you can begin anywhere and immediately apply what you learn.
* Presents dozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projects.
* Provides in-depth, practical coverage of essential data mining topics, including OLAP and data warehousing, data preprocessing, concept description, association rules, classification and prediction, and cluster analysis.
* Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields.
Table of contents:
PART I Overview of geographic data mining and knowledge discovery
1 Geographic data mining and knowledge discovery: an overview
HARVEY J.MILLER AND JIAWEI HAN
2 Paradigms for spatial and spatio-temporal data mining
JOHN F.RODDICK AND BRIAN G.LEES
PART II Geographic data warehouses and data depositories
3 Fundamentals of spatial data warehousing for geographic knowledge discovery
YVAN BÉDARD, TIM MERRETT AND JIAWEI HAN
4 Map cube: a visualization tool for spatial data warehouses S.SHEKHAR, C.T.LU, X.TAN, S.CHAWLA AND R.R.VATSAVAI
5 Making Internet-based depositories of geographical data usable with intelligent agent technology
RAJA R.SENGUPTA AND DAVID A.BENNETT
Colour Plate Section
PART III Techniques for geographic data mining and knowledge discovery
6 Modelling spatial dependencies for mining geospatial data: an introduction
SANJAY CHAWLA, SHASHI SHEKHAR, WEILI WU AND UYGAR OZESMI
7 Algorithms and applications for spatial data mining
MARTIN ESTER, HANS-PETER KRIEGEL AND JÖRG SANDER
8 Spatial clustering methods in data mining: a survey
JIAWEI HAN, MICHELINE KAMBER AND ANTHONY K.H.TUNG
9 Detecting outliers from large datasets
RAYMOND T.NG
PART IV Geographic knowledge discovery and geographic visualization
10 Geolnsight: an approach for developing a knowledge construction process based on the integration of GVis and KDD methods
MONICA WACHOWICZ
11 Visual exploration in geography: analysis with light
MARK GAHEGAN
PART V Applications of geographic data mining and knowledge discovery
12 Machine learning for information extraction from topographic maps
Donato Malerba, Floriana Esposito, Antonietta Lanza, and Francesca A. Lisi
13 Visualization based on the fuzzy ARTMAP neural network for mining remotely sensed data
SUCHARITA GOPAL, WEIGUO LIU AND CURTIS WOODCOCK
14 Mining mobile trajectories
CARL STEPHEN SMYTH
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