Temporal And Spatio-Temporal Data Mining

Temporal And Spatio-Temporal Data Mining

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Product Details

ISBN-13: 9781599043876
Publisher: IGI Global
Publication date: 03/25/2011
Pages: 294
Product dimensions: 7.00(w) x 10.20(h) x 0.80(d)

Table of Contents


Preface     vi
Introduction     1
Temporal Data Mining     3
Spatio-Temporal Data Mining     5
Organization of the Book     10
Time Series Mining: Background and Related Work   Minghua Zhang     14
Issues in Time Series Mining     15
Time Series Mining Techniques     21
Summary     37
Mining Dense Periodic Patterns in Time Series Databases   Chang Sheng     44
Notations and Definitions     45
Dense Periodicity     46
DPMiner     52
Experiment Evaluation     55
Summary     61
Mining Sequence Patterns in Evolving Databases   Minghua Zhang   Ben Kao   Chi-Lap Yip   David W. Cheung     63
Problem Definition     64
Algorithm MFS     66
Incremental Update Algorithms     69
Performance Study     72
Summary     85
Mining Progressive Confident Rules in Sequence Databases   Minghua Zhang     87
Problem Definition     91
Mining Concise Set of PCR     93
Experiments     99
Application of PCR inClassification     107
Summary     110
Early Works in Spatio-Temporal Mining     112
Spatio-Temporal Patterns     113
Review of Association Rule Mining     116
Spatial Association Pattern Mining     121
Summary     125
Mining Topological Patterns in Spatio-Temporal Databases     130
Problem Statement     132
Mining Topological Patterns     136
Algorithm ToplogyMiner     144
Experimental Study     148
Summary     155
Mining Flow Patterns in Spatio-Temporal Data     157
Notations and Terminologies     158
Flow Patterns     161
Mining Flow Patterns     163
Algorithm FlowMiner     174
Performance Study     176
Summary     187
Mining Generalized Flow Patterns     189
Notations and Terminologies     190
Generalized ST Patterns     193
Algorithm GenSTMiner     197
Performance Evaluation     201
Summary     207
Mining Spatio-Temporal Trees     209
Preliminaries     211
Related Work     215
Frequent Weak Sub-Tree Mining     216
Experimental Evaluation     220
Summary     224
Mining Spatio-Temporal Graph Patterns     227
Related Work     229
Preliminary Concepts     230
Partition-Based Graph Mining     232
Algorithm ParMiner     243
Incremental Mining Using PartMiner     245
Experimental Study     248
Summary     259
Conclusions and Future Work     262
Future Research Directions     263
About the Authors     266
Index     269

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