รายละเอียด:
Temporal and Spatio-Temporal Data Mining ISBN 9781599043876
Hardcover
Description
The recent surge of interest in spatio-temporal databases has resulted in numerous advances, such as: modeling, indexing, and querying of moving objects and spatio-temporal data. Aside from this, rule mining in spatial databases and temporal databases has been studied extensively in data mining research. Temporal and Spatio-Temporal Data Mining examines the problem of mining topological patterns in spatio-temporal databases by imposing the temporal constraints into the process of mining spatial collocation patterns. Temporal and Spatio-Temporal Data Mining presents probable solutions when discovering the spatial sequence patterns by incorporating the spatial information into the sequence of patterns, and introduces two new classes of spatial sequence patterns: flow patterns and generalized spatio-temporal patterns. This innovative book addresses different scenarios when finding complex relationships in spatio-temporal data by modeling them as graphs, giving readers a comprehensive synopsis on two successful partition-based algorithms designed by the authors.
Table of Contents
Chapter I Introduction
Temporal Data Mining
Spatio-Temporal Data Mining
Organization of the Book
Chapter II Time Series Mining : Background and Related Work
co-authored with Minghua Zhang, National University of Singapore, Singapore
Issues in Time Series Mining
Time Series Mining Techniques
Summary
Chapter III Mining Dense Periodic Patterns in Time Series Databases
co-authored with Chang Sheng, National University of Singapore, SingaporeSpatio-Temporal
Notations and Definitions
Dense Periodicity
DPMiner
Experiment Evaluation
Summary
Chapter IV Mining Sequence Patterns in Evolving Databases
contributed by Minghua Zhang, National University of Singapore, Singapore
Ben Kao, The University of Hong Kong, Hong Kong,
Chi-Lap Yip, The University of Honk Kong, Hong Kong, &
David W. Cheung, The University of Honk Kong, Hong Kong
Problem Definition
Algorithm MFSS
Incremental Update Algorithms
Performance Study
Summary
Chapter V Mining Progressive Confident Rules in Sequence Databases
co-authored with Minghua Zhang, National University of Singapore, Singapore
Problem Definition
Mining Concise Set of PCR
Experiments
Application of PCR in Classification
Summary
Chapter VI Early Works in Spatio-Temporal Mining
Spatio-Temporal Patterns
Review of Association Rule mining
Spatial Association Pattern mining
Summary
Chapter VII Mining Topological Patterns in Spatio-Temporal Databases
Problem Statement
Mining Topological Patterns
Algorithm TopologyMiner
Experimental Study
Summary
Chapter VIII Mining Flow Patterns in Spatio-Temporal Data
Notations and Terminologies
Flow Patterns
Mining Flow Patterns
Algorithm FlowMiner
Performance Study
Summary
Chapter IX Mining Generalized Flow Patterns
Notations and Terminologies
Generalized ST Patterns
Algorithm GenSTMiner
Performance Evaluation
Summary
Chapter X Mining Spatio-Temporal Trees
Preliminaries
Related Work
Frequent Weak Sub-Tree Mining
Experimental Evaluation
Summary
Chapter XI Mining Spatio-Temporal Graph Patterns
Related Work
Preliminary Concepts
Partition-Based Graph Mining
Algorithm PartMiner
Incremental Mining Using PartMiner
Experimental Study
Summary
Chapter XII Conclusions and Future Work
Future Research Directions