Spatiotemporal frequent pattern mining from evolving region trajectories. (2018)
- Record Type:
- Book
- Title:
- Spatiotemporal frequent pattern mining from evolving region trajectories. (2018)
- Main Title:
- Spatiotemporal frequent pattern mining from evolving region trajectories
- Further Information:
- Note: Berkay Aydin and Rafal A. Angryk.
- Authors:
- Aydin, Berkay
Angryk, Rafal. A - Contents:
- Intro; Preface; Acknowledgments; Contents; Acronyms; 1 A Gentle Introduction to Spatiotemporal Data Mining; 1.1 Types of Spatiotemporal Knowledge; 1.2 Motivation and Challenges; 1.2.1 Solar Physics; 1.2.2 Biomedical Sciences; 1.2.3 Epidemiology; 1.3 Challenges; 2 Modeling Spatiotemporal Trajectories; 2.1 Basic Spatiotemporal Data Types; 2.2 Moving Objects; 2.3 Evolving Region Trajectories; 2.3.1 Modeling Spatiotemporal Event Instances and Examples; 3 Modeling Spatiotemporal Relationships Among Trajectories; 3.1 Generic Spatial and Temporal Relationships; 3.1.1 Temporal Relationships 3.1.2 Spatial Relationships3.1.3 Spatial Co-locations; 3.2 Spatiotemporal Relationships; 3.2.1 Spatiotemporal Co-occurrence; 3.2.2 Spatiotemporal Sequences; 4 Significance Measurements for Spatiotemporal Co-occurrences; 4.1 The Family of Jaccard Measures; 4.1.1 J Measure; 4.1.2 J+ Measure; 4.1.3 J* Measure; 4.1.3.1 Key Properties of J*; 4.1.3.2 Antimonotonic Property; 4.1.3.3 Containment Property; 4.1.4 Algorithms for Calculating Jaccard-Derived Measures; 4.1.4.1 Calculating J; 4.1.4.2 Calculating J+; 4.1.4.3 Calculating J*; 4.2 Overlap Measures; 4.2.1 Key Properties of Overlap Measures 4.2.1.1 Antimonotonic Property4.2.1.2 Containment Property; 4.2.2 OMIN and OMAX Calculation Algorithms; 4.3 Cosine Measure; 4.3.1 Key Properties of Cosine Measure; 4.3.1.1 Antimonotonic Property; 4.3.1.2 Containment Property; 4.3.2 Algorithm for Calculating Cosine Measure; 4.4 Summary; 5 SpatiotemporalIntro; Preface; Acknowledgments; Contents; Acronyms; 1 A Gentle Introduction to Spatiotemporal Data Mining; 1.1 Types of Spatiotemporal Knowledge; 1.2 Motivation and Challenges; 1.2.1 Solar Physics; 1.2.2 Biomedical Sciences; 1.2.3 Epidemiology; 1.3 Challenges; 2 Modeling Spatiotemporal Trajectories; 2.1 Basic Spatiotemporal Data Types; 2.2 Moving Objects; 2.3 Evolving Region Trajectories; 2.3.1 Modeling Spatiotemporal Event Instances and Examples; 3 Modeling Spatiotemporal Relationships Among Trajectories; 3.1 Generic Spatial and Temporal Relationships; 3.1.1 Temporal Relationships 3.1.2 Spatial Relationships3.1.3 Spatial Co-locations; 3.2 Spatiotemporal Relationships; 3.2.1 Spatiotemporal Co-occurrence; 3.2.2 Spatiotemporal Sequences; 4 Significance Measurements for Spatiotemporal Co-occurrences; 4.1 The Family of Jaccard Measures; 4.1.1 J Measure; 4.1.2 J+ Measure; 4.1.3 J* Measure; 4.1.3.1 Key Properties of J*; 4.1.3.2 Antimonotonic Property; 4.1.3.3 Containment Property; 4.1.4 Algorithms for Calculating Jaccard-Derived Measures; 4.1.4.1 Calculating J; 4.1.4.2 Calculating J+; 4.1.4.3 Calculating J*; 4.2 Overlap Measures; 4.2.1 Key Properties of Overlap Measures 4.2.1.1 Antimonotonic Property4.2.1.2 Containment Property; 4.2.2 OMIN and OMAX Calculation Algorithms; 4.3 Cosine Measure; 4.3.1 Key Properties of Cosine Measure; 4.3.1.1 Antimonotonic Property; 4.3.1.2 Containment Property; 4.3.2 Algorithm for Calculating Cosine Measure; 4.4 Summary; 5 Spatiotemporal Co-occurrence Pattern (STCOP) Mining; 5.1 Preliminaries of STCOP Mining; 5.2 Significance and Prevalence Measurements; 5.3 STCOP Mining from Evolving Region Trajectories; 5.4 Efficient Spatiotemporal Joins for STCOP Mining; 5.4.1 Grid-Mapped Interval Trees (GITs) 5.4.2 Chebyshev Polynomial Indexing5.5 Summary; 6 Spatiotemporal Event Sequence (STES) Mining; 6.1 Modeling Spatiotemporal Event Sequences; 6.1.1 Head and Tail Window of an Instance; 6.1.2 Generating Head and Tail Windows; 6.1.3 Strategies for Head and Tail Window Generation; 6.1.3.1 Selection of the Segment: Interval-Based vs. Ratio-Based Generation; 6.1.3.2 Coverage Strategies: Partial, Full and Overfull; 6.1.3.3 Overlapping vs. Disjoint Coverage Strategies; 6.1.3.4 Temporal Propagation Strategies; 6.2 Spatiotemporal Follow Relationship and Measuring the Significance 6.2.1 Significance of Instance Sequences6.2.1.1 Temporal Algebra vs. Head and Tail Windows; 6.2.2 Prevalence of the Event Sequences; 6.3 Apriori-Based Algorithms for Mining Spatiotemporal Event Sequences; 6.3.1 Initialization; 6.3.2 SequenceConnect Algorithm; 6.3.3 Avoiding Spatiotemporal Joins; 6.4 A Pattern Growth-Based Approach for Mining Spatiotemporal Event Sequences; 6.4.1 Event Sequences and Graph Representation; 6.4.1.1 Graph Transformation; 6.4.2 EsGrowth Algorithm; 6.5 Mining the Most Prevalent Spatiotemporal Event Sequences: Top-(R%, K) Approach; 6.6 Summary; References; Index … (more)
- Publisher Details:
- Cham, Switzerland : Springer
- Publication Date:
- 2018
- Extent:
- 1 online resource, color illustrations
- Subjects:
- 006.312
Computer science
Spatial analysis (Statistics)
Data mining
Geospatial data
Geographic information systems
COMPUTERS / General
Science -- Earth Sciences -- Geography
Business & Economics -- Urban & Regional
Geographical information systems (GIS) & remote sensing
Political economy
Information systems
Geographical information systems
Regional economics
Computers -- Online Services -- General
Computer networking & communications
Electronic books - Languages:
- English
- ISBNs:
- 9783319998732
3319998730 - Related ISBNs:
- 9783319998725
3319998722 - Notes:
- Note: Includes bibliographical references and index.
Note: Online resource; title from PDF title page (EBSCO, viewed October 18, 2018). - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.342658
- Ingest File:
- 01_294.xml