Data Mining for Co-location Patterns

Principles and Applications
1. Auflage 2022
ISBN: 978-0-367-65426-9
Verlag: CRC Press

Buch, Englisch, 228 Seiten, Format (B × H): 161 mm x 240 mm, Gewicht: 514 g

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.

Zielgruppe

Academic, Postgraduate, Professional, Professional Practice & Development, and Undergraduate Advanced

Autoren/Hrsg.

Zhou, Guoqing

Fachgebiete

• Mathematik | Informatik EDV | Informatik Technische Informatik
• Technische Wissenschaften Umwelttechnik | Umwelttechnologie Umwelttechnik
• Geowissenschaften Umweltwissenschaften Umwelttechnik
• Mathematik | Informatik EDV | Informatik Informatik Theoretische Informatik
• Geowissenschaften Geologie GIS, Geoinformatik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining

Inhaltsverzeichnis

Chapter 1 Introduction

Chapter 2 Fundamentals of Mining Co-Location Patterns

Chapter 3 Principle of Mining Co-Location Patterns

Chapter 4 Manifold Learning Co-Location Pattern Mining

Chapter 5 Maximal Instance Co-Location Pattern Mining Algorithms

Chapter 6 Negative Co-Location Pattern Mining Algorithms

Chapter 7 Application of Mining Co-Location Patterns in Pavement Management and Rehabilitation

Chapter 8 Application of Mining Co-Location Patterns in Buffer Analysis

Chapter 9 Application of Mining Co-Location Patterns in Remotely Sensed Imagery Classification

Index

Über Autor(innen)

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.