About the Book:
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.
Table of Contents
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
