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140122 ||| eng |
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|a 9781461511496
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| 100 |
1 |
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|a Ladner, Roy
|e [editor]
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| 245 |
0 |
0 |
|a Mining Spatio-Temporal Information Systems
|h Elektronische Ressource
|c edited by Roy Ladner, Kevin Shaw, Mahdi Abdelguerfi
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| 250 |
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|a 1st ed. 2002
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| 260 |
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|a New York, NY
|b Springer US
|c 2002, 2002
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| 300 |
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|a X, 170 p
|b online resource
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| 505 |
0 |
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|a 1: Spatio-Temporal Data Mining and Knowledge Discovery: Issues Overview -- 1. Introduction -- 2. Background -- 3. Data -- 4. Data Issues -- 5. Conclusions -- 2: Indexing of Objects on the Move -- 1. Introduction -- 2. Problem Statement and Related Work -- 3. The TPR-Tree -- 4. The REXP-Tree -- 5. Summary of Performance Experiments -- 6. Conclusions -- 3: Efficient Storage of Large Volume Spatial and Temporal Point-Data in an Object-Oriented Database -- 1. Introduction -- 2. The GIDB System -- 3. The Problem Domain -- 4. An Object-Oriented Solution -- 5. Requirements -- 6. Towards a Solution -- 7. The Design -- 8. A Flexible Framework -- 9. Sample Applications -- 10. Evaluation -- 11. Future Developments -- 12. Conclusions -- 4: A Typology of Spatiotemporal Information Queries -- 1. Introduction -- 2. Spatiotemporal Information for the Dynamic World -- 3. A Typology of Spatiotemporal Queries -- 4. Conclusions -- 5: Visual Query of Time-Dependent 3D Weather in a Global Geospatial Environment -- 1. Introduction -- 2. 4D Data Model for the Visual Earth -- 3. Scalable, Hierarchical 3D Data Structure -- 4. Interactive, Accurate Visualization of Nonuniform Data -- 6: STQL — A Spatio-Temporal Query Language -- 1. Introduction -- 2. Related Work -- 3. The Data Model -- 4. Querying with Spatio-Temporal Operations -- 5. Visual Querying -- 6. Conclusions -- 7: Tripod: A Spatio-Historical Object Database System -- 1. Introduction -- 2. Case Study: UK National Land Use Database -- 3. The Tripod Object Model -- 4. Architecture -- 5. Related Work -- 6. Conclusions -- 8: Spatio-Temporal Subgroup Discovery -- 1. Introduction: Spatial Subgroup Mining -- 2. Application Example -- 3. Representation of Spatio-Temporal Data and of Spatial Subgroups -- 4. Spatio-Temporal Analyses -- 5. Database Integration -- 6. Conclusions and Future Work
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| 653 |
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|a Geographical Information System
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| 653 |
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|a Information Storage and Retrieval
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Data Structures and Information Theory
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| 653 |
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|a Information storage and retrieval systems
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| 653 |
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|a Information theory
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Geographic information systems
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| 653 |
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|a Data structures (Computer science)
|
| 700 |
1 |
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|a Shaw, Kevin
|e [editor]
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| 700 |
1 |
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|a Abdelguerfi, Mahdi
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b SBA
|a Springer Book Archives -2004
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| 490 |
0 |
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|a The Springer International Series in Engineering and Computer Science
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| 028 |
5 |
0 |
|a 10.1007/978-1-4615-1149-6
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-1-4615-1149-6?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 003.54
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| 082 |
0 |
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|a 005.73
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| 520 |
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|a Mining Spatio-Temporal Information Systems, an edited volume is composed of chapters from leading experts in the field of Spatial-Temporal Information Systems and addresses the many issues in support of modeling, creation, querying, visualizing and mining. Mining Spatio-Temporal Information Systems is intended to bring together a coherent body of recent knowledge relating to STIS data modeling, design, implementation and STIS in knowledge discovery. In particular, the reader is exposed to the latest techniques for the practical design of STIS, essential for complex query processing. Mining Spatio-Temporal Information Systems is structured to meet the needs of practitioners and researchers in industry and graduate-level students in Computer Science
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