Foundations of multidimensional and metric data structures:
Gespeichert in:
1. Verfasser: | |
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Format: | Buch |
Sprache: | English |
Veröffentlicht: |
Amsterdam [u.a.]
Morgan Kaufmann Publ.
2006
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Schriftenreihe: | The Morgan Kaufmann series in computer graphics and geometric modeling
The Morgan Kaufmann series in data management systems |
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis Publisher description Table of contents only Inhaltsverzeichnis |
Beschreibung: | transferred to digital printing in 2011 Includes bibliographical references and index |
Beschreibung: | XXVII, 993 S. Ill., graph. Darst. |
ISBN: | 0123694469 9780123694461 |
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100 | 1 | |a Samet, Hanan |e Verfasser |0 (DE-588)1016975856 |4 aut | |
245 | 1 | 0 | |a Foundations of multidimensional and metric data structures |c Hanan Samet |
264 | 1 | |a Amsterdam [u.a.] |b Morgan Kaufmann Publ. |c 2006 | |
300 | |a XXVII, 993 S. |b Ill., graph. Darst. | ||
336 | |b txt |2 rdacontent | ||
337 | |b n |2 rdamedia | ||
338 | |b nc |2 rdacarrier | ||
490 | 0 | |a The Morgan Kaufmann series in computer graphics and geometric modeling | |
490 | 0 | |a The Morgan Kaufmann series in data management systems | |
500 | |a transferred to digital printing in 2011 | ||
500 | |a Includes bibliographical references and index | ||
650 | 4 | |a Algorithmes | |
650 | 7 | |a Algoritmos e estruturas de dados |2 larpcal | |
650 | 7 | |a Estruturas de dados |2 larpcal | |
650 | 4 | |a Structures de données (Informatique) | |
650 | 4 | |a Data structures (Computer science) | |
650 | 4 | |a Computer algorithms | |
650 | 0 | 7 | |a Datenstruktur |0 (DE-588)4011146-5 |2 gnd |9 rswk-swf |
655 | 7 | |0 (DE-588)4123623-3 |a Lehrbuch |2 gnd-content | |
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Datensatz im Suchindex
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adam_text | FOUNDATIONS OF MULTIDIMENSIONAL AND METRIE DATA STRUCTURES HANAN SAMET
UNIVERSITY OF MARYLAND, COLLEGE PARK 14 ELSEVIER MORGAN KAUFMANN
PUBLISHERS IS AN IMPRINT OF ELSEVIER MORGAN KAUFMANN PUBLISHERS
AMSTERDAM * BOSTON * HEIDELBERG * LONDON NEW YORK * OXFORD * PARIS * SAN
DIEGO SAN FRANCISCO * SINGAPORE * SYDNEY * TOKYO » CONTENTS FOREWORD XV
PREFACE XVII 1 MULTIDIMENSIONAL POINT DATA I 1.1 INTRODUCTION 5 1.2
RANGE TREES 14 1.3 PRIORITY SEARCH TREES 19 1.4 QUADTREES 28 1.4.1 POINT
QUADTREES 28 1.4.1.1 INSERTION 28 1.4.1.2 DELETION 31 1.4.1.3 SEARCH 36
1.4.2 TRIE-BASED QUADTREES 37 1.4.2.1 MXQUADTREE 38 1.4.2.2 PR QUADTREES
42 1.4.3 COMPARISON OF POINT AND TRIE-BASED QUADTREES 47 1.5 K-D TREES
48 1.5.1 POINT K-D TREES 50 1.5.1.1 INSERTION 50 1.5.1.2 DELETION 52
1.5.1.3 SEARCH 55 1.5.1.4 POINT K-D TREE VARIANTS 57 1.5.2 TRIE-BASED
K-D TREES 70 1.5.2.1 PR K-D TREE 71 1.5.2.2 SLIDING-MIDPOINT K-D TREE 72
1.5.2.3 BUECKET PR K-D TREE AND PMR K-D TREE 74 1.5.2.4 PATH-COMPRESSED
PR K-D TREE 75 1.5.2.5 PATH-LEVEL COMPRESSED PR K-D TREE 77 1.5.2.6
BD-TREES 79 1.5.2.7 BALANCED BOX-DECOMPOSITION TREE (BBD-TREE) 83 1.5.3
CONJUGATION TREE 88 1.6 ONE-DIMENSIONAL ORDERINGS 90 1.7 BUECKET METHODS
95 1.7.1 TREE DIRECTORY METHODS 96 1.7.1.1 K-D-B-TREE 98 1.7.1.2 HYBRID
TREE 101 1.7.1.3 LSD TREE 102 1.7.1.4 HB-TREE 106 1.7.1.5 K-D-B-TRIES HO
1.7.1.6 BV-TREE 116 1.7.1.6.1 DEFINITION 117 1.7.1.6.2 BUILDING A
BV-TREE 120 IX CONTENTS 1.7.1.6.3 SEARCHING A BV-TREE 122 1.7.1.6.4
PERFORMANCE 125 1.7.1.6.5 SUMMARY 127 1.7.1.7 STARK METHODS 129 1.7.2
GRID DIRECTORY METHODS 130 1.7.2.1 GRIDFILE 131 1.7.2.2 EXCELL 137
1.7.2.3 LINEAR HASHING 140 1.7.2.3.1 ADAPTING LINEAR HASHING TO
MULTIDIMENSIONAL DATA . . . 140 1.7.2.3.2 MULTIDIMENSIONAL EXTENDIBLE
HASHING (MDEH) . . . . 146 1.7.2.3.3 DYNAMIC Z HASHING 150 1.7.2.3.4
LINEAR HASHING WITH PARTIAL EXPANSIONS (LHPE) . . . . 152 1.7.2.4
ALTERNATIVE IMPLEMENTATIONSOF LINEAR HASHING 152 1.7.2.4.1 QUANTILE
HASHING 153 1.7.2.4.2 PIECEWISE LINEAR ORDER PRESERVING (PLOP) HASHING .
. 154 1.7.2.4.3 SPIRAL HASHING 156 1.7.2.4.4 SUMMARY 159 1.7.2.5
COMPARISON 160 1.7.3 STORAGE UTILIZATION 163 1.8 PK-TREES 164 1.8.1
MOTIVATION 165 1.8.2 OVERVIEW 167 1.8.3 DEFINITION 169 1.8.4 COMPARISON
WITH BUECKET METHODS 170 1.8.5 OPERATIONS 171 1.8.5.1 REPRESENTATION AND
SEARCHING 172 1.8.5.2 INSERTION 172 1.8.5.3 DELETION 178 1.8.6
DISCUSSION 181 1.9 CONCLUSION 184 2 OBJECT-BASED AND IMAGE-BASED IMAGE
REPRESENTATIONS . 191 2.1 INTERIOR-BASED REPRESENTATIONS 193 2.1.1
UNIT-SIZE CELLS 194 2.1.1.1 CELL SHAPES AND TILINGS 196 2.1.1.2 ORDERING
SPACE 199 2.1.1.3 ARRAY ACCESS STRUCTURES 202 2.1.1.4 TREE ACCESS
STRUCTURES 203 2.1.2 BLOCKS 204 2.1.2.1 DECOMPOSITION INTO ARBITRATILY
SIZED RECTANGULAR BLOCKS . . . . 205 2.1.2.2 MEDIAL AXIS TRANSFORMATION
(MAT) 208 2.1.2.3 IRREGULAER GRID 210 2.1.2.4 REGION QUADTREE AND REGION
OCTREE 211 2.1.2.5 ATREE 220 2.1.2.6 BINTREE 221 2.1.2.7 ADAPTATION OF
THE POINT QUADTREE FOR REGIONS 222 2.1.2.8 ADAPTATION OF THE K-D TREE
FOR REGIONS 223 2.1.2.9 X-Y TREE, TREEMAP, AND PUZZLETREE 225 2.1.2.10
HEXAGONAL BLOCKS 230 2.1.2.11 TRIANGULAER BLOCKS 231 2.1.3 NONORTHOGONAL
BLOCKS 232 2.1.3.1 BSP TREE 233 2.1.3.2 K-STRUCTURE 237 2.1.3.3
SEPARATING CHAIN 242 2.1.3.3.1 OVERVIEW 242 2.1.3.3.2 LAYEREDDAG 248
2.1.4 ARBITRARY OBJECTS 254 2.1.4.1 COVERAGE-BASED SPLITTING 255 2.1.4.2
DENSITY-BASED SPLITTING 260 2.1.5 HIERARCHICAL INTERIOR-BASED
REPRESENTATIONS 264 * 2.1.5.1 IMAGE-BASED HIERARCHICAL INTERIOR-BASED
REPRESENTATIONS (PYRAMIDS) 266 2.1.5.2 OBJECT-BASED HIERARCHICAL
INTERIOR-BASED REPRESENTATIONS (R-TREES, BOUNDING BOX HIERARCHIES) 270
2.1.5.2.1 OVERVIEW 271 2.1.5.2.2 ORDERING-BASED AGGREGATION TECHNIQUES
275 2.1.5.2.3 EXTENT-BASED AGGREGATION TECHNIQUES 282 2.1.5.2.4 R*-TREE
289 2.1.5.2.5 BULK INSERTION 296 2.1.5.2.6 BULKLOADING 299 2.1.5.2.7
SHORTCOMINGS AND SOLUTIONS 301 2.1.5.3 DISJOINT OBJECT-BASED
HIERARCHICAL INTERIOR-BASED REPRESENTATIONS (K-D-B-TREE, R+-TREE, AND
CELL TREE) 304 2.2 BOUNDARY-BASED REPRESENTATIONS 312 2.2.1 THE BOUNDARY
MODEL (BREP) 315 2.2.1.1 OVERVIEW 315 2.2.1.2 EDGE-BASED METHODS USING
WINGED EDGES 317 2.2.1.3 VERTEX-BASED AND FACE-BASED METHODS USING LATHS
329 2.2.1.3.1 LATH DATA STRUCTURES FOR MANIFOLD OBJECTS 331 2.2.1.3.2
LATH DATA STRUCTURES FOR MESHES WITH BOUNDARIES . . . 336 2.2.1.3.3
SUMMARY 341 2.2.1.4 VORONOI DIAGRAMS, DELAUNAY GRAPHS, AND DELAUNAY
TRIANGULATIONS 346 2.2.1.5 CONSTRAINED AND CONFORMING DELAUNAY
TRIANGULATIONS 350 2.2.1.6 DELAUNAY TETRAHEDRALIZATIONS 352 2.2.1.7
APPLICATIONS OF THE WINGED-EDGE DATA STRUCTURE (TRIANGLE TABLE, CORNER
TABLE) 353 2.2.2 IMAGE-BASED BOUNDARY REPRESENTATIONS 355 2.2.2.1
LINEQUADTREE 356 2.2.2.2 MX QUADTREE AND MX OCTREE 357 2.2.2.3 EDGE
QUADTREE 359 2.2.2.4 FACE OCTREE 361 2.2.2.5 ADAPTIVELY SAMPLED DISTANCE
FIELDS 362 2.2.2.6 PMQUADTREES 365 2.2.2.7 PM OCTREE 369 2.2.2.8 BUECKET
PM QUADTREE AND PMR QUADTREE 374 2.2.2.9 SECTORTREE 377 2.2.2.10 CONE
TREE 380 2.2.3 OBJECT-BASED BOUNDARY REPRESENTATIONS 382 2.2.3.1 STRIP
TREE, ARE TREE, AND BSPR 382 2.2.3.2 PRISMTREE 386 2.2.3.3 HALTREE 389
2.2.3.4 SIMPLIFICATION METHODS AND DATA STRUCTURES 391 2.2.4
SURFACE-BASED BOUNDARY REPRESENTATIONS 399 2.3 DIFFERENCE-BASED
COMPACTION METHODS 408 2.3.1 RUNLENGTH ENCODING 409 2.3.2 CHAIN CODE 416
2.3.3 VERTEX REPRESENTATION 417 2.4 HISTORICAL OVERVIEW 423 3 INTERVALS
AND SMALL RECTANGLES 427 3.1 PLANE-SWEEP METHODS AND THE RECTANGLE
INTERSECTION PROBLEM 428 3.1.1 SEGMENT TREE 430 3.1.2 INTERVALTREE 434
3.1.3 PRIORITY SEARCH TREE 439 3.1.4 ALTERNATIVE SOLUTIONS AND RELATED
PROBLEMS 443 3.2 PLANE-SWEEP METHODS AND THE MEASURE PROBLEM 447 3.3
POINT-BASED METHODS 453 3.3.1 REPRESENTATIVE POINTS 453 3.3.2
COLLECTIONS OF REPRESENTATIVE POINTS 459 3.3.2.1 CORNER STITCHING 459
CONTENTS 3.3.2.2 BALANCED FOUR-DIMENSIONAL K-D TREE 460 3.3.2.3 GRIDFILE
462 3.3.2.4 LSD TREE 463 3.3.2.5 TWO-DIMENSIONAL REPRESENTATIONS 463
3.3.3 SUMMARY 464 3.4 AREA-BASED METHODS 466 3.4.1 MX-CIF QUADTREE 466
3.4.1.1 DEFINITION 466 3.4.1.2 OPERATIONS 468 3.4.1.3 COMPARISON WITH
OTHER REPRESENTATIONS 473 3.4.2 ALTERNATIVES TO THE MX-CIF QUADTREE 474
3.4.3 MULTIPLE QUADTREE BLOCK REPRESENTATIONS 480 4 HIGH-DIMENSIONAL
DATA 485 4.1 BEST-FIRST NEAREST NEIGHBOR FINDING 490 4.1.1 MOTIVATION
491 4.1.2 SEARCH HIERARCHY 492 4.1.3 ALGORITHM 493 4.1.4 ALGORITHM WITH
DUPLICATE INSTANCES OF OBJECTS 499 4.1.5 ALGORITHM EXTENSIONS
(AE -NEAREST, AET-FARTHEST, SKYLINES) 502 4.1.6 NEAREST NEIGHBORS IN A
SPATIAL NETWORK 508 4.1.7 RELATED WORK 516 4.2 THE DEPTH-FIRST
A -NEAREST NEIGHBOR ALGORITHM 517 4.2.1 BASIC ALGORITHM 518 4.2.2
PRUNINGRULES 521 4.2.3 EFFECTS OF CLUSTERING METHODS ON PRUNING 529
4.2.4 ORDERING THE PROCESSING OF THE ELEMENTS OF THE ACTIVE LIST 534
4.2.5 IMPROVED ALGORITHM 538 4.2.6 INCORPORATING MAXNEARESTDIST IN A
BEST-FIRST ALGORITHM 548 4.2.7 EXAMPLE 553 4.2.8 COMPARISON 554 4.3
APPROXIMATE NEAREST NEIGHBOR FINDING 557 4.4 MULTIDIMENSIONAL INDEXING
METHODS 566 4.4.1 X-TREE 566 4.4.2 BOUNDING SPHERE METHODS: SPHERE TREE,
SS-TREE, BALLTREE, AND SR-TREE . . 567 4.4.3 INCREASING THE FANOUT:
TV-TREE, HYBRID TREE, AND A-TREE 572 4.4.4 METHODS BASED ON THE VORONOI
DIAGRAM: OS-TREE 573 4.4.5 APPROXIMATE VORONOI DIAGRAM (AVD) 580 4.4.6
AVOIDING OVERLAPPING ALL OF THE LEAF BLOCKS 585 4.4.7 PYRAMID TECHNIQUE
587 4.4.8 METHODS BASED ON A SEQUENTIAL SCAN 592 4.5 DISTANCE-BASED
INDEXING METHODS 598 4.5.1 DISTANCE METRIE AND SEARCH PRUNING 600 4.5.2
BALL PARTITIONING METHODS 604 4.5.2.1 VP-TREE 604 4.5.2.1.1 STRUCTURE
604 4.5.2.1.2 SEARCH 606 4.5.2.2 VP SB -TREE 607 4.5.2.3 MVP-TREE 608
4.5.2.4 OTHER METHODS RELATED TO BALL PARTITIONING 609 4.5.3 GENERALIZED
HYPERPLANE PARTITIONING METHODS 613 4.5.3.1 GH-TREE 613 4.5.3.2 GNAT 616
4.5.3.3 BISECTOR TREE AND MB-TREE 617 4.5.3.4 OTHER METHODS RELATED TO
GENERALIZED HYPERPLANE PARTITIONING . . 622 4.5.4 M-TREE 624 4.5.4.1
STRUCTURE 624 4.5.4.2 SEARCH 626 4.5.5 SA-TREE 629 4.5.5.1 DEFINITION
630 4.5.5.2 SEARCH 633 XII ,T 4.5.6 KNN GRAPH 637 CONTENTS 4.5.7
DISTANCE MATRIX METHODS 643 4.5.7.1 AESA 643 4.5.7.2 LAESA 646 4.5.7.3
OTHER DISTANCE MATRIX METHODS 647 4.5.8 SASH: INDEXING WITHOUT USING THE
TRIANGLE INEQUALITY 650 4.6 DIMENSION REDUCTION METHODS 662 4.6.1
SEARCHING IN THE DIMENSION REDUCED SPACE 664 4.6.1.1 RANGE QUERIES 664
4.6.1.2 NEAREST NEIGHBOR QUERIES 665 4.6.2 USING ONLY ONE DIMENSION 668
4.6.3 REPRESENTATIVE POINT METHODS 670 4.6.4 TRANSFORMATION INTO A
DIFFERENT AND SMALLER FEATURE SET 671 4.6.4.1 SVD 671 4.6.4.2 DISCRETE
FOURIER TRANSFORM (DFT) 676 4.6.5 SUMMARY 685 4.7 EMBEDDING METHODS 685
4.7.1 INTRODUCTION 687 4.7.2 LIPSCHITZ EMBEDDINGS 691 4.7.2.1 DEFINITION
691 4.7.2.2 SELECTING REFERENCE SETS 692 4.7.2.3 EXAMPLE OF A LIPSCHITZ
EMBEDDING 693 4.7.2.4 SPARSEMAP 694 4.7.3 FASTMAP 697 4.7.3.1 MECHANICS
OF FASTMAP 697 4.7.3.2 CHOOSING PIVOT OBJECTS 698 4.7.3.3 DERIVING THE
FIRST COORDINATE VALUE 699 4.7.3.4 PROJECTED DISTANCE 700 4.7.3.5
SUBSEQUENT ITERATIONS 701 4.7.3.6 PRUNING PROPERTY 703 4.7.3.7 EXPANSION
707 4.7.3.8 HEURISTIC FOR NON-EUCLIDEAN METRICS 708 4.7.3.9 SUMMARY AND
COMPARISON WITH OTHER EMBEDDINGS 709 4.7.4 LOCALITY SENSITIVE HASHING
711 APPENDIX A: OVERVIEW OF B-TREES 717 APPENDIX B: LINEAR HASHING 729
APPENDIX C: SPIRAL HASHING 735 APPENDIX D: DESCRIPTION OF PSEUDOCODE
LANGUAGE 743 SOLUTIONS TO EXERCISES 747 REFERENCES 877 REFERENCE KEYWORD
INDEX 947 AUTHOR AND CREDIT INDEX 953 SUBJECT INDEX 969 XIII
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adam_txt |
FOUNDATIONS OF MULTIDIMENSIONAL AND METRIE DATA STRUCTURES HANAN SAMET
UNIVERSITY OF MARYLAND, COLLEGE PARK 14 ELSEVIER MORGAN KAUFMANN
PUBLISHERS IS AN IMPRINT OF ELSEVIER MORGAN KAUFMANN PUBLISHERS
AMSTERDAM * BOSTON * HEIDELBERG * LONDON NEW YORK * OXFORD * PARIS * SAN
DIEGO SAN FRANCISCO * SINGAPORE * SYDNEY * TOKYO » CONTENTS FOREWORD XV
PREFACE XVII 1 MULTIDIMENSIONAL POINT DATA I 1.1 INTRODUCTION 5 1.2
RANGE TREES 14 1.3 PRIORITY SEARCH TREES 19 1.4 QUADTREES 28 1.4.1 POINT
QUADTREES 28 1.4.1.1 INSERTION 28 1.4.1.2 DELETION 31 1.4.1.3 SEARCH 36
1.4.2 TRIE-BASED QUADTREES 37 1.4.2.1 MXQUADTREE 38 1.4.2.2 PR QUADTREES
42 1.4.3 COMPARISON OF POINT AND TRIE-BASED QUADTREES 47 1.5 K-D TREES
48 1.5.1 POINT K-D TREES 50 1.5.1.1 INSERTION 50 1.5.1.2 DELETION 52
1.5.1.3 SEARCH 55 1.5.1.4 POINT K-D TREE VARIANTS 57 1.5.2 TRIE-BASED
K-D TREES 70 1.5.2.1 PR K-D TREE 71 1.5.2.2 SLIDING-MIDPOINT K-D TREE 72
1.5.2.3 BUECKET PR K-D TREE AND PMR K-D TREE 74 1.5.2.4 PATH-COMPRESSED
PR K-D TREE 75 1.5.2.5 PATH-LEVEL COMPRESSED PR K-D TREE 77 1.5.2.6
BD-TREES 79 1.5.2.7 BALANCED BOX-DECOMPOSITION TREE (BBD-TREE) 83 1.5.3
CONJUGATION TREE 88 1.6 ONE-DIMENSIONAL ORDERINGS 90 1.7 BUECKET METHODS
95 1.7.1 TREE DIRECTORY METHODS 96 1.7.1.1 K-D-B-TREE 98 1.7.1.2 HYBRID
TREE 101 1.7.1.3 LSD TREE 102 1.7.1.4 HB-TREE 106 1.7.1.5 K-D-B-TRIES HO
1.7.1.6 BV-TREE 116 1.7.1.6.1 DEFINITION 117 1.7.1.6.2 BUILDING A
BV-TREE 120 IX CONTENTS 1.7.1.6.3 SEARCHING A BV-TREE 122 1.7.1.6.4
PERFORMANCE 125 1.7.1.6.5 SUMMARY 127 1.7.1.7 STARK METHODS 129 1.7.2
GRID DIRECTORY METHODS 130 1.7.2.1 GRIDFILE 131 1.7.2.2 EXCELL 137
1.7.2.3 LINEAR HASHING 140 1.7.2.3.1 ADAPTING LINEAR HASHING TO
MULTIDIMENSIONAL DATA . . . 140 1.7.2.3.2 MULTIDIMENSIONAL EXTENDIBLE
HASHING (MDEH) . . . . 146 1.7.2.3.3 DYNAMIC Z HASHING 150 1.7.2.3.4
LINEAR HASHING WITH PARTIAL EXPANSIONS (LHPE) . . . . 152 1.7.2.4
ALTERNATIVE IMPLEMENTATIONSOF LINEAR HASHING 152 1.7.2.4.1 QUANTILE
HASHING 153 1.7.2.4.2 PIECEWISE LINEAR ORDER PRESERVING (PLOP) HASHING .
. 154 1.7.2.4.3 SPIRAL HASHING 156 1.7.2.4.4 SUMMARY 159 1.7.2.5
COMPARISON 160 1.7.3 STORAGE UTILIZATION 163 1.8 PK-TREES 164 1.8.1
MOTIVATION 165 1.8.2 OVERVIEW 167 1.8.3 DEFINITION 169 1.8.4 COMPARISON
WITH BUECKET METHODS 170 1.8.5 OPERATIONS 171 1.8.5.1 REPRESENTATION AND
SEARCHING 172 1.8.5.2 INSERTION 172 1.8.5.3 DELETION 178 1.8.6
DISCUSSION 181 1.9 CONCLUSION 184 2 OBJECT-BASED AND IMAGE-BASED IMAGE
REPRESENTATIONS . 191 2.1 INTERIOR-BASED REPRESENTATIONS 193 2.1.1
UNIT-SIZE CELLS 194 2.1.1.1 CELL SHAPES AND TILINGS 196 2.1.1.2 ORDERING
SPACE 199 2.1.1.3 ARRAY ACCESS STRUCTURES 202 2.1.1.4 TREE ACCESS
STRUCTURES 203 2.1.2 BLOCKS 204 2.1.2.1 DECOMPOSITION INTO ARBITRATILY
SIZED RECTANGULAR BLOCKS . . . . 205 2.1.2.2 MEDIAL AXIS TRANSFORMATION
(MAT) 208 2.1.2.3 IRREGULAER GRID 210 2.1.2.4 REGION QUADTREE AND REGION
OCTREE 211 2.1.2.5 ATREE 220 2.1.2.6 BINTREE 221 2.1.2.7 ADAPTATION OF
THE POINT QUADTREE FOR REGIONS 222 2.1.2.8 ADAPTATION OF THE K-D TREE
FOR REGIONS 223 2.1.2.9 X-Y TREE, TREEMAP, AND PUZZLETREE 225 2.1.2.10
HEXAGONAL BLOCKS 230 2.1.2.11 TRIANGULAER BLOCKS 231 2.1.3 NONORTHOGONAL
BLOCKS 232 2.1.3.1 BSP TREE 233 2.1.3.2 K-STRUCTURE 237 2.1.3.3
SEPARATING CHAIN 242 2.1.3.3.1 OVERVIEW 242 2.1.3.3.2 LAYEREDDAG 248
2.1.4 ARBITRARY OBJECTS 254 2.1.4.1 COVERAGE-BASED SPLITTING 255 2.1.4.2
DENSITY-BASED SPLITTING 260 2.1.5 HIERARCHICAL INTERIOR-BASED
REPRESENTATIONS 264 * 2.1.5.1 IMAGE-BASED HIERARCHICAL INTERIOR-BASED
REPRESENTATIONS (PYRAMIDS) 266 2.1.5.2 OBJECT-BASED HIERARCHICAL
INTERIOR-BASED REPRESENTATIONS (R-TREES, BOUNDING BOX HIERARCHIES) 270
2.1.5.2.1 OVERVIEW 271 2.1.5.2.2 ORDERING-BASED AGGREGATION TECHNIQUES
275 2.1.5.2.3 EXTENT-BASED AGGREGATION TECHNIQUES 282 2.1.5.2.4 R*-TREE
289 2.1.5.2.5 BULK INSERTION 296 2.1.5.2.6 BULKLOADING 299 2.1.5.2.7
SHORTCOMINGS AND SOLUTIONS 301 2.1.5.3 DISJOINT OBJECT-BASED
HIERARCHICAL INTERIOR-BASED REPRESENTATIONS (K-D-B-TREE, R+-TREE, AND
CELL TREE) 304 2.2 BOUNDARY-BASED REPRESENTATIONS 312 2.2.1 THE BOUNDARY
MODEL (BREP) 315 2.2.1.1 OVERVIEW 315 2.2.1.2 EDGE-BASED METHODS USING
WINGED EDGES 317 2.2.1.3 VERTEX-BASED AND FACE-BASED METHODS USING LATHS
329 2.2.1.3.1 LATH DATA STRUCTURES FOR MANIFOLD OBJECTS 331 2.2.1.3.2
LATH DATA STRUCTURES FOR MESHES WITH BOUNDARIES . . . 336 2.2.1.3.3
SUMMARY 341 2.2.1.4 VORONOI DIAGRAMS, DELAUNAY GRAPHS, AND DELAUNAY
TRIANGULATIONS 346 2.2.1.5 CONSTRAINED AND CONFORMING DELAUNAY
TRIANGULATIONS 350 2.2.1.6 DELAUNAY TETRAHEDRALIZATIONS 352 2.2.1.7
APPLICATIONS OF THE WINGED-EDGE DATA STRUCTURE (TRIANGLE TABLE, CORNER
TABLE) 353 2.2.2 IMAGE-BASED BOUNDARY REPRESENTATIONS 355 2.2.2.1
LINEQUADTREE 356 2.2.2.2 MX QUADTREE AND MX OCTREE 357 2.2.2.3 EDGE
QUADTREE 359 2.2.2.4 FACE OCTREE 361 2.2.2.5 ADAPTIVELY SAMPLED DISTANCE
FIELDS 362 2.2.2.6 PMQUADTREES 365 2.2.2.7 PM OCTREE 369 2.2.2.8 BUECKET
PM QUADTREE AND PMR QUADTREE 374 2.2.2.9 SECTORTREE 377 2.2.2.10 CONE
TREE 380 2.2.3 OBJECT-BASED BOUNDARY REPRESENTATIONS 382 2.2.3.1 STRIP
TREE, ARE TREE, AND BSPR 382 2.2.3.2 PRISMTREE 386 2.2.3.3 HALTREE 389
2.2.3.4 SIMPLIFICATION METHODS AND DATA STRUCTURES 391 2.2.4
SURFACE-BASED BOUNDARY REPRESENTATIONS 399 2.3 DIFFERENCE-BASED
COMPACTION METHODS 408 2.3.1 RUNLENGTH ENCODING 409 2.3.2 CHAIN CODE 416
2.3.3 VERTEX REPRESENTATION 417 2.4 HISTORICAL OVERVIEW 423 3 INTERVALS
AND SMALL RECTANGLES 427 3.1 PLANE-SWEEP METHODS AND THE RECTANGLE
INTERSECTION PROBLEM 428 3.1.1 SEGMENT TREE 430 3.1.2 INTERVALTREE 434
3.1.3 PRIORITY SEARCH TREE 439 3.1.4 ALTERNATIVE SOLUTIONS AND RELATED
PROBLEMS 443 3.2 PLANE-SWEEP METHODS AND THE MEASURE PROBLEM 447 3.3
POINT-BASED METHODS 453 3.3.1 REPRESENTATIVE POINTS 453 3.3.2
COLLECTIONS OF REPRESENTATIVE POINTS 459 3.3.2.1 CORNER STITCHING 459
CONTENTS 3.3.2.2 BALANCED FOUR-DIMENSIONAL K-D TREE 460 3.3.2.3 GRIDFILE
462 3.3.2.4 LSD TREE 463 3.3.2.5 TWO-DIMENSIONAL REPRESENTATIONS 463
3.3.3 SUMMARY 464 3.4 AREA-BASED METHODS 466 3.4.1 MX-CIF QUADTREE 466
3.4.1.1 DEFINITION 466 3.4.1.2 OPERATIONS 468 3.4.1.3 COMPARISON WITH
OTHER REPRESENTATIONS 473 3.4.2 ALTERNATIVES TO THE MX-CIF QUADTREE 474
3.4.3 MULTIPLE QUADTREE BLOCK REPRESENTATIONS 480 4 HIGH-DIMENSIONAL
DATA 485 4.1 BEST-FIRST NEAREST NEIGHBOR FINDING 490 4.1.1 MOTIVATION
491 4.1.2 SEARCH HIERARCHY 492 4.1.3 ALGORITHM 493 4.1.4 ALGORITHM WITH
DUPLICATE INSTANCES OF OBJECTS 499 4.1.5 ALGORITHM EXTENSIONS
(AE'-NEAREST, AET-FARTHEST, SKYLINES) 502 4.1.6 NEAREST NEIGHBORS IN A
SPATIAL NETWORK 508 4.1.7 RELATED WORK 516 4.2 THE DEPTH-FIRST
A"-NEAREST NEIGHBOR ALGORITHM 517 4.2.1 BASIC ALGORITHM 518 4.2.2
PRUNINGRULES 521 4.2.3 EFFECTS OF CLUSTERING METHODS ON PRUNING 529
4.2.4 ORDERING THE PROCESSING OF THE ELEMENTS OF THE ACTIVE LIST 534
4.2.5 IMPROVED ALGORITHM 538 4.2.6 INCORPORATING MAXNEARESTDIST IN A
BEST-FIRST ALGORITHM 548 4.2.7 EXAMPLE 553 4.2.8 COMPARISON 554 4.3
APPROXIMATE NEAREST NEIGHBOR FINDING 557 4.4 MULTIDIMENSIONAL INDEXING
METHODS 566 4.4.1 X-TREE 566 4.4.2 BOUNDING SPHERE METHODS: SPHERE TREE,
SS-TREE, BALLTREE, AND SR-TREE . . 567 4.4.3 INCREASING THE FANOUT:
TV-TREE, HYBRID TREE, AND A-TREE 572 4.4.4 METHODS BASED ON THE VORONOI
DIAGRAM: OS-TREE 573 4.4.5 APPROXIMATE VORONOI DIAGRAM (AVD) 580 4.4.6
AVOIDING OVERLAPPING ALL OF THE LEAF BLOCKS 585 4.4.7 PYRAMID TECHNIQUE
587 4.4.8 METHODS BASED ON A SEQUENTIAL SCAN 592 4.5 DISTANCE-BASED
INDEXING METHODS 598 4.5.1 DISTANCE METRIE AND SEARCH PRUNING 600 4.5.2
BALL PARTITIONING METHODS 604 4.5.2.1 VP-TREE 604 4.5.2.1.1 STRUCTURE
604 4.5.2.1.2 SEARCH 606 4.5.2.2 VP SB -TREE 607 4.5.2.3 MVP-TREE 608
4.5.2.4 OTHER METHODS RELATED TO BALL PARTITIONING 609 4.5.3 GENERALIZED
HYPERPLANE PARTITIONING METHODS 613 4.5.3.1 GH-TREE 613 4.5.3.2 GNAT 616
4.5.3.3 BISECTOR TREE AND MB-TREE 617 4.5.3.4 OTHER METHODS RELATED TO
GENERALIZED HYPERPLANE PARTITIONING . . 622 4.5.4 M-TREE 624 4.5.4.1
STRUCTURE 624 4.5.4.2 SEARCH 626 4.5.5 SA-TREE 629 4.5.5.1 DEFINITION
630 4.5.5.2 SEARCH 633 XII ,T 4.5.6 KNN GRAPH 637 CONTENTS 4.5.7
DISTANCE MATRIX METHODS 643 4.5.7.1 AESA 643 4.5.7.2 LAESA 646 4.5.7.3
OTHER DISTANCE MATRIX METHODS 647 4.5.8 SASH: INDEXING WITHOUT USING THE
TRIANGLE INEQUALITY 650 4.6 DIMENSION REDUCTION METHODS 662 4.6.1
SEARCHING IN THE DIMENSION REDUCED SPACE 664 4.6.1.1 RANGE QUERIES 664
4.6.1.2 NEAREST NEIGHBOR QUERIES 665 4.6.2 USING ONLY ONE DIMENSION 668
4.6.3 REPRESENTATIVE POINT METHODS 670 4.6.4 TRANSFORMATION INTO A
DIFFERENT AND SMALLER FEATURE SET 671 4.6.4.1 SVD 671 4.6.4.2 DISCRETE
FOURIER TRANSFORM (DFT) 676 4.6.5 SUMMARY 685 4.7 EMBEDDING METHODS 685
4.7.1 INTRODUCTION 687 4.7.2 LIPSCHITZ EMBEDDINGS 691 4.7.2.1 DEFINITION
691 4.7.2.2 SELECTING REFERENCE SETS 692 4.7.2.3 EXAMPLE OF A LIPSCHITZ
EMBEDDING 693 4.7.2.4 SPARSEMAP 694 4.7.3 FASTMAP 697 4.7.3.1 MECHANICS
OF FASTMAP 697 4.7.3.2 CHOOSING PIVOT OBJECTS 698 4.7.3.3 DERIVING THE
FIRST COORDINATE VALUE 699 4.7.3.4 PROJECTED DISTANCE 700 4.7.3.5
SUBSEQUENT ITERATIONS 701 4.7.3.6 PRUNING PROPERTY 703 4.7.3.7 EXPANSION
707 4.7.3.8 HEURISTIC FOR NON-EUCLIDEAN METRICS 708 4.7.3.9 SUMMARY AND
COMPARISON WITH OTHER EMBEDDINGS 709 4.7.4 LOCALITY SENSITIVE HASHING
711 APPENDIX A: OVERVIEW OF B-TREES 717 APPENDIX B: LINEAR HASHING 729
APPENDIX C: SPIRAL HASHING 735 APPENDIX D: DESCRIPTION OF PSEUDOCODE
LANGUAGE 743 SOLUTIONS TO EXERCISES 747 REFERENCES 877 REFERENCE KEYWORD
INDEX 947 AUTHOR AND CREDIT INDEX 953 SUBJECT INDEX 969 XIII |
any_adam_object | 1 |
any_adam_object_boolean | 1 |
author | Samet, Hanan |
author_GND | (DE-588)1016975856 |
author_facet | Samet, Hanan |
author_role | aut |
author_sort | Samet, Hanan |
author_variant | h s hs |
building | Verbundindex |
bvnumber | BV021755324 |
callnumber-first | Q - Science |
callnumber-label | QA76 |
callnumber-raw | QA76.9.D35 |
callnumber-search | QA76.9.D35 |
callnumber-sort | QA 276.9 D35 |
callnumber-subject | QA - Mathematics |
classification_rvk | ST 265 |
classification_tum | DAT 455f |
ctrlnum | (OCoLC)61731525 (DE-599)BVBBV021755324 |
dewey-full | 005.7/3 |
dewey-hundreds | 000 - Computer science, information, general works |
dewey-ones | 005 - Computer programming, programs, data, security |
dewey-raw | 005.7/3 |
dewey-search | 005.7/3 |
dewey-sort | 15.7 13 |
dewey-tens | 000 - Computer science, information, general works |
discipline | Informatik |
discipline_str_mv | Informatik |
format | Book |
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genre_facet | Lehrbuch |
id | DE-604.BV021755324 |
illustrated | Illustrated |
index_date | 2024-07-02T15:33:17Z |
indexdate | 2024-07-09T20:43:18Z |
institution | BVB |
isbn | 0123694469 9780123694461 |
language | English |
lccn | 2005054165 |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-014968489 |
oclc_num | 61731525 |
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physical | XXVII, 993 S. Ill., graph. Darst. |
publishDate | 2006 |
publishDateSearch | 2006 |
publishDateSort | 2006 |
publisher | Morgan Kaufmann Publ. |
record_format | marc |
series2 | The Morgan Kaufmann series in computer graphics and geometric modeling The Morgan Kaufmann series in data management systems |
spelling | Samet, Hanan Verfasser (DE-588)1016975856 aut Foundations of multidimensional and metric data structures Hanan Samet Amsterdam [u.a.] Morgan Kaufmann Publ. 2006 XXVII, 993 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier The Morgan Kaufmann series in computer graphics and geometric modeling The Morgan Kaufmann series in data management systems transferred to digital printing in 2011 Includes bibliographical references and index Algorithmes Algoritmos e estruturas de dados larpcal Estruturas de dados larpcal Structures de données (Informatique) Data structures (Computer science) Computer algorithms Datenstruktur (DE-588)4011146-5 gnd rswk-swf (DE-588)4123623-3 Lehrbuch gnd-content Datenstruktur (DE-588)4011146-5 s DE-604 http://www.gbv.de/dms/ilmenau/toc/500625727.PDF Inhaltsverzeichnis http://www.loc.gov/catdir/enhancements/fy0625/2005054165-d.html Publisher description http://www.loc.gov/catdir/enhancements/fy0625/2005054165-t.html Table of contents only GBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014968489&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
spellingShingle | Samet, Hanan Foundations of multidimensional and metric data structures Algorithmes Algoritmos e estruturas de dados larpcal Estruturas de dados larpcal Structures de données (Informatique) Data structures (Computer science) Computer algorithms Datenstruktur (DE-588)4011146-5 gnd |
subject_GND | (DE-588)4011146-5 (DE-588)4123623-3 |
title | Foundations of multidimensional and metric data structures |
title_auth | Foundations of multidimensional and metric data structures |
title_exact_search | Foundations of multidimensional and metric data structures |
title_exact_search_txtP | Foundations of multidimensional and metric data structures |
title_full | Foundations of multidimensional and metric data structures Hanan Samet |
title_fullStr | Foundations of multidimensional and metric data structures Hanan Samet |
title_full_unstemmed | Foundations of multidimensional and metric data structures Hanan Samet |
title_short | Foundations of multidimensional and metric data structures |
title_sort | foundations of multidimensional and metric data structures |
topic | Algorithmes Algoritmos e estruturas de dados larpcal Estruturas de dados larpcal Structures de données (Informatique) Data structures (Computer science) Computer algorithms Datenstruktur (DE-588)4011146-5 gnd |
topic_facet | Algorithmes Algoritmos e estruturas de dados Estruturas de dados Structures de données (Informatique) Data structures (Computer science) Computer algorithms Datenstruktur Lehrbuch |
url | http://www.gbv.de/dms/ilmenau/toc/500625727.PDF http://www.loc.gov/catdir/enhancements/fy0625/2005054165-d.html http://www.loc.gov/catdir/enhancements/fy0625/2005054165-t.html http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014968489&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
work_keys_str_mv | AT samethanan foundationsofmultidimensionalandmetricdatastructures |
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