Data Mining for Co-location Patterns

Principles and Applications

Häftad, Engelska, 2024

Av Guoqing Zhou

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Co-location pattern mining detects sets of features frequently located in close proximity to each other. This book focuses on data mining for co-location pattern, a valid method for identifying patterns from all types of data and applying them in business intelligence and analytics. It explains the fundamentals of co-location pattern mining, co-location decision tree, and maximal instance co-location pattern mining along with an in-depth overview of data mining, machine learning, and statistics. This arrangement of chapters helps readers understand the methods of co-location pattern mining step-by-step and their applications in pavement management, image classification, geospatial buffer analysis, etc.

Produktinformation

Utgivningsdatum2024-05-27
Mått156 x 234 x 13 mm
Vikt420 g
FormatHäftad
SpråkEngelska
Antal sidor228
FörlagTaylor & Francis Ltd
ISBN9780367688660

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Guoqing Zhou received his first PhD from Wuhan University, Wuhan, China, in 1994 and his second PhD from Virginia Tech at Blacksburg, Virginia, USA, in 2001. He was a visiting scholar at the Department of Computer Science and Technology, Tsinghua University, Beijing, China, and a postdoctoral researcher at the Institute of Information Science, Beijing Jiaotong University, Beijing, China, from 1994–1996. He continued his research as an Alexander von Humboldt Fellow at the Technical University of Berlin, Berlin, Germany, from 1997–1998 and afterward became a postdoctoral researcher at the Ohio State University, Columbus, OH, USA, from 1998 to 2000. Later he worked at Old Dominion University, Norfolk, VA, USA, as an assistant professor, associate professor, and full professor in 2000, 2005, and 2010, respectively. He is currently professor at the Guilin University of Technology, Guilin, China. He is author of five books and has published more than 300 papers in peer-reviewed journals and conference proceedings.

Chapter 1 IntroductionChapter 2 Fundamentals of Mining Co-Location PatternsChapter 3 Principle of Mining Co-Location PatternsChapter 4 Manifold Learning Co-Location Pattern MiningChapter 5 Maximal Instance Co-Location Pattern Mining AlgorithmsChapter 6 Negative Co-Location Pattern Mining AlgorithmsChapter 7 Application of Mining Co-Location Patterns in Pavement Management and RehabilitationChapter 8 Application of Mining Co-Location Patterns in Buffer AnalysisChapter 9 Application of Mining Co-Location Patterns in Remotely Sensed Imagery ClassificationIndex