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by Philipp Meisen (Author)
About the Author
Philipp Meisen holds a doctoral degree from RWTH Aachen, where he was a research group leader at the Chair of Information Management in Mechanical Engineering.
About this book
Philipp Meisen introduces a model, a query language, and a similarity measure enabling users to analyze time interval data. The introduced tools are combined to design and realize an information system. The presented system is capable of performing analytical tasks (avoiding any type of summarizability problems), providing insights, and visualizing results processing millions of intervals within milliseconds using an intuitive SQL-based query language. The heart of the solution is based on several bitmap-based indexes, which enable the system to handle huge amounts of time interval data.
Brief contents
1 Introduction and Motivation 1
2 Time Interval Data Analysis 7
2.1 Time 7
2.1.1 Time Intervals 7
2.1.2 Time Interval Data Aggregation 10
2.1.3 Temporal Models 14
2.1.4 Temporal Operators 20
2.1.5 Temporal Concepts 22
2.1.6 Special Characteristics of Time 23
2.2 Features of Time Interval Data Analysis Information System 29
2.2.1 Analytical Capabilities 30
2.2.2 Time Interval Data Analysis Process 35
2.2.3 User Interface, Visualization, and User Interactions 42
2.3 Summary 43
3 State of the Art 45
3.1 Analytical Information Systems 45
3.2 Analyzing Time Interval Data: Different Approaches 46
3.2.1 On-Line Analytical Processing 47
3.2.2 Temporal Pattern Mining & Association Rule Mining 52
3.2.3 Visual Analytics 54
3.3 Performance Improvements 56
3.3.1 Indexing Time Interval Data 56
3.3.2 Aggregating Time Interval Data 60
3.3.3 Caching Time Interval Data 61
3.4 Analytical Query Languages for Temporal Data 62
3.5 Similarity of Time Interval Data 67
3.6 Summary 70
4 TIDAMODEL: Modeling Time Interval Data 73
4.1 Time Axis 73
4.2 Descriptors 76
4.3 Time Interval Database 80
4.4 Dimensional Modeling 82
4.5 Summary 87
5 TIDAQL: Querying for Time Interval Data 91
5.1 Data Control Language 92
5.2 Data Definition Language 95
5.3 Data Manipulation Language 96
5.3.1 Insert, Delete, & Update Statements 97
5.3.2 Get & Alive Statements 99
5.3.3 Select Statements 100
5.4 Summary 108
6 TIDADISTANCE: Similarity of Time Interval Data 111
6.1 Temporal Order Distance 113
6.2 Temporal Relational Distance 115
6.3 Temporal Measure Distance 117
6.4 Temporal Similarity Measure 118
7 TIDAIS: An Information System for Time Interval Data 121
7.1 System’s Architecture, Components, and Implementation 121
7.1.1 Data Repository 125
7.1.2 Cache & Storage 127
7.2 Configuration 129
7.2.1 Model Configuration 130
7.2.2 System Configuration 145
7.3 Data Structures & Algorithms 149
7.3.1 Model Handling 150
7.3.2 Indexes 156
7.3.3 Caching & Storage 165
7.3.4 Aggregation Techniques 167
7.3.5 Distance Calculation 171
7.4 User Interfaces 176
7.5 Summary 178
8 Results & Evaluation 181
8.1 Requirements & Features 181
8.2 Performance 187
8.2.1 High Performance Collections 188
8.2.2 Load Performance 189
8.2.3 Selection Performance 190
8.2.4 Distance Performance 196
8.2.5 Proprietary Solutions vs. TIDAIS 197
8.3 Summary 201
9 Summary and Outlook 203
Appendix 205
Pipelined Table Functions (PL/SQL Oracle) 205
A Complete Sample Model-Configuration-File 206
A Complete Sample Configuration-File 211
Detailed Overview of the Runtime Performance 215
3-NN of the Temporal Relational Similarity 217
Pages: 232 pages
Publisher: Springer Vieweg; 1st ed. 2016 edition (September 14, 2016)
Language: English
ISBN-10: 9783658157272
ISBN-13: 978-3658157272
Springer__Analyzing Time Interval Data.pdf
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