Temporal and spatio-temporal data mining:
"This book presents probable solutions when discovering the spatial sequence patterns by incorporating the information into the sequence of patterns, and introduces new classes of spatial sequence patterns, called flow and generalized spatio-temporal patterns, addressing different scenarios in...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Hershey ; New York
IGI Publ.
2008
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Zusammenfassung: | "This book presents probable solutions when discovering the spatial sequence patterns by incorporating the information into the sequence of patterns, and introduces new classes of spatial sequence patterns, called flow and generalized spatio-temporal patterns, addressing different scenarios in spatio-temporal data by modeling them as graphs, providing a comprehensive synopsis on two successful partition-based algorithms designed by the authors"--Provided by publisher. |
| Beschreibung: | Includes bibliographical references and index |
| Beschreibung: | X, 280 S. graph. Darst. |
| ISBN: | 9781599043876 |
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| 520 | 3 | |a "This book presents probable solutions when discovering the spatial sequence patterns by incorporating the information into the sequence of patterns, and introduces new classes of spatial sequence patterns, called flow and generalized spatio-temporal patterns, addressing different scenarios in spatio-temporal data by modeling them as graphs, providing a comprehensive synopsis on two successful partition-based algorithms designed by the authors"--Provided by publisher. | |
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Datensatz im Suchindex
| _version_ | 1804138040035115008 |
|---|---|
| adam_text | Temporal
and
Spatio-Temporal
Data Mining
Table
of
Contents
Preface
...........................................................................................................................
vi
Chapter I. Introduction
................................................................................................]
Temporal Data Mining
.........................................................................................
і
Spatio-Temporal Data
Mining
.............................................................................5
Organization of the Book
...................................................................................10
Chapter
11.
Time Series Mining: Background and Related Work
.........................14
co-authored with Minghua Zhang, National University of Singapore,
Singapore
Issues in Time Series Mining
............................................................................../5
Time Series Mining Techniques
..........................................................................21
Summary
.............................................................................................................37
Chapter III. Mining Dense Periodic Patterns in Time Series Databases
...............44
co-authored with Chang Sheng, National University of Singapore, Singapore
Notations and Definitions
...................................................................................45
Dense Periodicity
...............................................................................................46
DPMiner
.............................................................................................................52
Experiment Evaluation
.......................................................................................55
Summary
.............................................................................................................61
Chapter IV. Mining Sequence Patterns in Evolving Databases
..............................63
contributed by Minghua Zhang, National University of Singapore, Singapore,
Ben
Kao,
The University of Hong Kong, Hong Kong,
Chi-Lap Yip, The University of Hong Kong, Hong Kong,
&
David W. Cheung, The University of Hong Kong, Hong Kong
Problem Definition
.............................................................................................64
Algorithm MFS
...................................................................................................66
Incremental Update Algorithms
.........................................................................69
Performance Study
.............................................................................................72
Summary
.............................................................................................................85
Chapter V. Mining Progressive Confident Rules in Sequence Databases
..............87
co-authored with Minghua Zhang, National University of Singapore,
Singapore
Problem Definition
.............................................................................................91
Mining Concise Set of PCR
................................................................................93
Experiments
........................................................................................................99
Application of PCR in Classification
...............................................................107
Summary
...........................................................................................................
HO
Chapter VI. Early Works in
Spatio-Temporal
Mining
..........................................112
Spatio-Temporal
Patterns
................................................................................
ИЗ
Review of Association Rule Mining
..................................................................
J
16
Spatial Association Pattern Mining
.................................................................121
Summary
...........................................................................................................125
Chapter
VII.
Mining Topological Patterns in
Spatio-Temporal
Databases
.........130
Problem Statement
...........................................................................................132
Mining Topological Patterns
............................................................................136
Algorithm TopologyMiner
................................................................................144
Experimental Study
..........................................................................................148
Summary
...........................................................................................................155
Chapter
VIII.
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
Chapter IX. Mining Generalized Flow Patterns
....................................................189
Notations and Terminologies
...........................................................................190
Generalized ST Patterns
..................................................................................193
Algorithm GenSTMiner
....................................................................................197
Performance Evaluation
..................................................................................201
Summary
...........................................................................................................207
Chapter X. Mining
Spatio-Temporal
Trees
............................................................209
Preliminaries
....................................................................................................211
Related Work
....................................................................................................215
Frequent Weak Sub-Tree Mining
......................................................................216
Experimental Evaluation
..................................................................................220
Summary
...........................................................................................................224
Chapter XI. Mining
Spatio-Temporal
Graph Patterns
.........................................227
Related Work
....................................................................................................229
Preliminary Concepts
.......................................................................................230
Partition-Based
Graph
Mining
........................................................................232
Algorithm PartMiner
........................................................................................243
Incremental Mining Using PartMiner
..............................................................245
Experimental Study
..........................................................................................248
Summary
...........................................................................................................259
Chapter
XII.
Conclusions and Future Work
..........................................................262
Future Research Directions
..............................................................................263
About the Authors
.....................................................................................................266
Index
..........................................................................................................................269
|
| adam_txt |
Temporal
and
Spatio-Temporal
Data Mining
Table
of
Contents
Preface
.
vi
Chapter I. Introduction
.]
Temporal Data Mining
.
і
Spatio-Temporal Data
Mining
.5
Organization of the Book
.10
Chapter
11.
Time Series Mining: Background and Related Work
.14
co-authored with Minghua Zhang, National University of Singapore,
Singapore
Issues in Time Series Mining
./5
Time Series Mining Techniques
.21
Summary
.37
Chapter III. Mining Dense Periodic Patterns in Time Series Databases
.44
co-authored with Chang Sheng, National University of Singapore, Singapore
Notations and Definitions
.45
Dense Periodicity
.46
DPMiner
.52
Experiment Evaluation
.55
Summary
.61
Chapter IV. Mining Sequence Patterns in Evolving Databases
.63
contributed by Minghua Zhang, National University of Singapore, Singapore,
Ben
Kao,
The University of Hong Kong, Hong Kong,
Chi-Lap Yip, The University of Hong Kong, Hong Kong,
&
David W. Cheung, The University of Hong Kong, Hong Kong
Problem Definition
.64
Algorithm MFS
.66
Incremental Update Algorithms
.69
Performance Study
.72
Summary
.85
Chapter V. Mining Progressive Confident Rules in Sequence Databases
.87
co-authored with Minghua Zhang, National University of Singapore,
Singapore
Problem Definition
.91
Mining Concise Set of PCR
.93
Experiments
.99
Application of PCR in Classification
.107
Summary
.
HO
Chapter VI. Early Works in
Spatio-Temporal
Mining
.112
Spatio-Temporal
Patterns
.
ИЗ
Review of Association Rule Mining
.
J
16
Spatial Association Pattern Mining
.121
Summary
.125
Chapter
VII.
Mining Topological Patterns in
Spatio-Temporal
Databases
.130
Problem Statement
.132
Mining Topological Patterns
.136
Algorithm TopologyMiner
.144
Experimental Study
.148
Summary
.155
Chapter
VIII.
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
Chapter IX. Mining Generalized Flow Patterns
.189
Notations and Terminologies
.190
Generalized ST Patterns
.193
Algorithm GenSTMiner
.197
Performance Evaluation
.201
Summary
.207
Chapter X. Mining
Spatio-Temporal
Trees
.209
Preliminaries
.211
Related Work
.215
Frequent Weak Sub-Tree Mining
.216
Experimental Evaluation
.220
Summary
.224
Chapter XI. Mining
Spatio-Temporal
Graph Patterns
.227
Related Work
.229
Preliminary Concepts
.230
Partition-Based
Graph
Mining
.232
Algorithm PartMiner
.243
Incremental Mining Using PartMiner
.245
Experimental Study
.248
Summary
.259
Chapter
XII.
Conclusions and Future Work
.262
Future Research Directions
.263
About the Authors
.266
Index
.269 |
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| indexdate | 2024-07-09T21:21:51Z |
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| isbn | 9781599043876 |
| language | English |
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| spelling | Hsu, Wynne Verfasser aut Temporal and spatio-temporal data mining Wynne Hsu ; Mong Li Lee ; Junmei Wang Hershey ; New York IGI Publ. 2008 X, 280 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier Includes bibliographical references and index "This book presents probable solutions when discovering the spatial sequence patterns by incorporating the information into the sequence of patterns, and introduces new classes of spatial sequence patterns, called flow and generalized spatio-temporal patterns, addressing different scenarios in spatio-temporal data by modeling them as graphs, providing a comprehensive synopsis on two successful partition-based algorithms designed by the authors"--Provided by publisher. Data mining Temporal databases Data Mining (DE-588)4428654-5 gnd rswk-swf Data Mining (DE-588)4428654-5 s DE-604 Lee, Mong Li Verfasser (DE-588)131628313 aut Wang, Junmei Verfasser aut Erscheint auch als Online-Ausgabe 978-1-59904-389-0 Digitalisierung UB Bayreuth application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016753748&sequence=000008&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Hsu, Wynne Lee, Mong Li Wang, Junmei Temporal and spatio-temporal data mining Data mining Temporal databases Data Mining (DE-588)4428654-5 gnd |
| subject_GND | (DE-588)4428654-5 |
| title | Temporal and spatio-temporal data mining |
| title_auth | Temporal and spatio-temporal data mining |
| title_exact_search | Temporal and spatio-temporal data mining |
| title_exact_search_txtP | Temporal and spatio-temporal data mining |
| title_full | Temporal and spatio-temporal data mining Wynne Hsu ; Mong Li Lee ; Junmei Wang |
| title_fullStr | Temporal and spatio-temporal data mining Wynne Hsu ; Mong Li Lee ; Junmei Wang |
| title_full_unstemmed | Temporal and spatio-temporal data mining Wynne Hsu ; Mong Li Lee ; Junmei Wang |
| title_short | Temporal and spatio-temporal data mining |
| title_sort | temporal and spatio temporal data mining |
| topic | Data mining Temporal databases Data Mining (DE-588)4428654-5 gnd |
| topic_facet | Data mining Temporal databases Data Mining |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=016753748&sequence=000008&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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