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" Spatial data management / "
Nikos Mamoulis
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BL
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| Record Number
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646347
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dltt
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| Main Entry
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Mamoulis, Nikos
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| Title & Author
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Spatial data management /\ Nikos Mamoulis
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| Publication Statement
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[San Rafael, Calif.] :: Morgan & Claypool Publishers,, c2012
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| Series Statement
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Synthesis lectures on data management,; #21
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| Page. NO
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xiv, 133 p. :: ill. ;; 24 cm
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| ISBN
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1608458326 (pbk.)
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: 9781608458325 (pbk.)
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: 9781608458332 (ebook)
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: 1608458334 (ebook)
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| Notes
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Part of: Synthesis digital library of engineering and computer science
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| Bibliographies/Indexes
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Includes bibliographical references (p. 119-132)
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| Contents
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1. Introduction -- 1.1 Spatial data types, predicates, and queries -- 1.2 Extending a DBMS to an SDBMS -- 1.3 Historical evolution of research and systems development -- 1.4 Summary and outline -- 2. Spatial data -- 2.1 Spatial relationships -- 2.1.1 Topological relationships -- 2.1.2 Directional relationships -- 2.1.3 Distance relationships -- 2.2 Spatial queries -- 2.3 Issues in spatial query processing -- 2.3.1 Extent or not? -- 2.4 Summary -- 3. Indexing -- 3.1 Point access methods -- 3.1.1 The grid file -- 3.1.2 Space filling curves -- 3.1.3 The quadtree -- 3.2 Indexing objects with extent -- 3.3 The R-tree -- 3.3.1 Optimization of the R-tree structure -- 3.3.2 The R*-tree: an optimized version of the R-tree -- 3.3.3 Bulk-loading R-trees -- 3.4 Summary -- 4. Spatial query evaluation -- 4.1 Spatial selections -- 4.2 Nearest neighbor queries -- 4.2.1 A depth-first nearest neighbor search algorithm -- 4.2.2 A best-first nearest neighbor search algorithm -- 4.2.3 K-nearest neighbor search and incremental search -- 4.3 Spatial joins -- 4.3.1 Index-based methods -- 4.3.2 Algorithms that do not consider indexes -- 4.3.3 Single-index join methods -- 4.3.4 A unified spatial join approach -- 4.3.5 Comparison of spatial join algorithms -- 4.3.6 The refinement step of a spatial join -- 4.3.7 Distance joins and related queries -- 4.4 Query optimization -- 4.4.1 Selectivity estimation -- 4.4.2 Cost estimation for spatial query operations -- 4.5 Summary -- 5. Spatial networks -- 5.1 Modeling spatial networks -- 5.2 Disk-based indexing approaches -- 5.3 Shortest path computation -- 5.3.1 Dijkstras algorithm -- 5.3.2 A* search -- 5.3.3 Bi-directional search -- 5.3.4 Speeding-up search by preprocessing -- 5.3.5 Query points on graph edges -- 5.4 Evaluation of spatial queries over spatial networks -- 5.4.1 Distance-based spatial selection -- 5.4.2 Nearest-neighbor retrieval -- 5.4.3 Join queries -- 5.5 Path materialization techniques -- 5.5.1 Hierarchical path materialization -- 5.5.2 Compressing and indexing materialized paths -- 5.5.3 Embedding methods -- 5.6 Summary -- 6. Applications of spatial data management technology -- 6.1 Spatio-temporal data management -- 6.1.1 Models and queries for spatio-temporal data -- 6.1.2 Indexing -- 6.2 High dimensional data management -- 6.2.1 Similarity measures and queries -- 6.2.2 Multi-dimensional indexes and the curse of dimensionality -- 6.2.3 Gemini: generic multimedia object indexing -- 6.3 Multi-criteria ranking -- 6.3.1 Top-k and skyline evaluation using spatial access methods -- 6.3.2 Spatially ranking data -- 6.4 Data mining and OLAP -- 6.4.1 Classification -- 6.4.2 Clustering -- 6.4.3 Association rules mining -- 6.4.4 Spatial aggregation and on-line analytical processing -- 6.5 Privacy-preserving publication of microdata -- 6.6 Spatial information retrieval -- 6.6.1 The inverted file -- 6.6.2 Ranking by relevance -- 6.6.3 Indexing for ranking queries -- 6.6.4 Spatial keyword search -- 6.7 Summary
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| Abstract
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Spatial database management deals with the storage, indexing, and querying of data with spatial features, such as location and geometric extent. Many applications require the efficient management of spatial data, including Geographic Information Systems, Computer Aided Design, and Location Based Services. The goal of this book is to provide the reader with an overview of spatial data management technology, with an emphasis on indexing and search techniques. It first introduces spatial data models and queries and discusses the main issues of extending a database system to support spatial data. It presents indexing approaches for spatial data, with a focus on the R-tree. Query evaluation and optimization techniques for the most popular spatial query types (selections, nearest neighbor search, and spatial joins) are portrayed for data in Euclidean spaces and spatial networks. The book concludes by demonstrating the ample application of spatial data management technology on a wide range of related application domains: management of spatio-temporal data and high-dimensional feature vectors, multi-criteria ranking, data mining and OLAP, privacy-preserving data publishing, and spatial keyword search
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| Subject
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Spatial data infrastructures
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Geospatial data
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Database management
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| Dewey Classification
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910.285
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| LC Classification
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G70.217.G46M257 2012
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