Fundamentals of database indexing and searching:
Gespeichert in:
| 1. Verfasser: | |
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| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Boca Raton
CRC Press
2016
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| Ausgabe: | 1. issued in paperback |
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | xxxi, 252 Seiten Illustrationen, Diagramme 24 cm |
| ISBN: | 1138033952 9781138033955 |
Internformat
MARC
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Datensatz im Suchindex
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| adam_text | Contents List of Figures xix List of Tables xxi List of Key Concepts List of Examples Preface 1 Basics Database Queries 1.1 Basic Setting..................................................................... 1.2 Exact Search...................................................................... 1.3 Similarity Search............................................................... 1.4 Join.................................................................................... 1.5 Errors................................................................................. 1.5.1 Error Parameters................................................... 1.5.2 ROC Curve............................................................ II 2 xxv xxvii Acknowledgments I xxiii Low-Dimensional Index Structures xxxi 1 3 3 4 4 6 7 8 11 13 Hashing 15 2.1 16 16 16 17 17 17 18 19 20 2.2 Static Hashing .................................................................. 2.1.1 Chaining ............................................................... 2.1.2 Open Addressing................................................... 2.1.3 Problems of Static Hashing................................. Dynamic Hashing ............................................................ 2.2.1 Dynamic Hashing................................................... 2.2.2 Extendible Hashing ............................................. 2.2.2.1 Searching and Insertion........................ 2.2.3 Linear Hashing...................................................... ix
x 3 Contents Contents 2.2.3.1 Searching................................................. 2.2.3.2 Insertion................................................. 2.3 Locality Sensitive Hashing(LSH) ................................... 2.3.1 Hamming Space ................................................... 2.3.2 E2LSH .................................................................. 2.4 Multi-Dimensional Hashing............................................. 2.4.1 Grid File ............................................................... 2.4.1.1 Searching................................................. 2.4.1.2 Insertion................................................. 2.5 Space-Filling Curves......................................................... 2.5.1 Desirable Properties............................................. 2.5.2 Examples............................................................... 2.5.3 Properties............................................................... 21 22 22 24 26 27 27 28 28 29 29 29 30 Memory-Based Index Structures 33 3.1 33 34 34 36 37 37 38 38 39 40 40 41 41 42 42 43 43 44 44 45 46 47 48 50 51 52 53 53 Index Structures............................................................... 3.1.1 Properties of Index Structures ........................... 3.1.2 Classification of Index Structures........................ 3.2 BinarySearch Tree (BST) .............................................. 3.2.1 Searching............................................................... 3.2.2 Insertion.................................................................. 3.2.3
Discussion............................................................... 3.2.4 Balanced Binary Search Tree.............................. 3.3 Quadtree ........................................................................... 3.3.1 Insertion.................................................................. 3.3.2 Searching............................................................... 3.3.3 Variants and Extensions....................................... 3.3.4 Discussion............................................................... 3.4 K-D-Tree........................................................................... 3.4.1 Insertion.................................................................. 3.4.2 Searching............................................................... 3.4.3 Variants.................................................................. 3.5 Range Tree......................................................................... 3.5.1 Range Searching................................................... 3.5.2 Multi-Dimensional Range Tree........................... 3.5.3 Multi-Dimensional Range Searching.................. 3.6 Voronoi Diagram............................................................... 3.6.1 Construction......................................................... 3.6.2 Extensions and Variants....................................... 3.7 Tries ................................................................................. 3.7.1 Searching............................................................... 3.7.2
Variants.................................................................. 3.7.3 Discussion............................................................... 3.8 Suffix Tree ........................................................................... 54 3.8.1 Searching............................................................... 55 3.8.2 Construction......................................................... 55 Bitmap Index ...................................................................... 56 3.9 III 4 xi Disk-Based Index Structures 59 Hierarchical Structures 61 4.1 4.2 61 64 64 64 65 66 66 66 67 68 69 70 71 72 73 73 74 75 76 76 76 77 77 77 78 78 78 79 79 80 80 81 81 82 82 4.3 4.4 4.5 4.6 4.7 В-Tree and B֊b-Tree............................................................. K-D-B-Tree........................................................................... 4.2.1 Structure............................................................... 4.2.2 Splitting.................................................................. 4.2.3 Deletion.................................................................. 4.2.4 Searching............................................................... 4.2.5 Discussion............................................................... General Framework .................................................... 4.3.1 Point Queries......................................................... 4.3.2 Range Queries ...................................................... 4.3.3 Nearest Neighbor Queries.................................... 4.3.3.1 Best-First Search
................................. 4.3.3.2IncrementalNearest Neighbor Queries . 4.3.4 Window Queries................................................... 4.3.5 Minimum Bounding Geometries ........................ R-Tree .............................................................................. 4.4.1 Structure............................................................... 4.4.2 Searching............................................................... 4.4.3 Insertion.................................................................. 4.4.4 Deletion.................................................................. 4.4.5 Update .................................................................. 4.4.6 Splitting.................................................................. 4.4.6.1 Exhaustive Split..................................... 4.4.6.2 Quadratic Split........................................ 4.4.6.3 Linear Split.............................................. 4.4.7 Discussion............................................................... R*-Tree.............................................................................. 4.5.1 Insertion.................................................................. 4.5.2 Splitting.................................................................. 4.5.3 Forced Re-Insertion ............................................. R+-Tree ........................................................................... 4.6.1 Structure............................................................... 4.6.2
Discussion............................................................... Hiłbert R-Tree .................................................................. 4.7.1 Splitting..................................................................
Contents xii 4.7.2 Discussion................................................................. SS-Tree................................................................................. SR-Tree................................................................................. 4.9.1 Structure................................................................. 4.9.2 Searching................................................................. 4.9.3 Discussion................................................................. 4.10 P-Tree ................................................................................. 4.11 Bulk-Loading........................................................................ 4.11.1 Generic Framework.................................................. 4.11.2 STR Algorithm........................................................ 4.11.3 Bulk-Loading in High Dimensions ...................... 4.8 4.9 IV 5 Distances Distance Functions 5.1 5.2 5.3 5.4 5.5 5.6 5.7 5.8 6 Metric Spaces ..................................................................... Lp Norm .............................................................................. 5.2.1 Normalized Euclidean Distance............................ Quadratic Form Distance .................................................. 5.3.1 Mahalanobis Distance............................................ Cosine Similarity................................................................. Statistical Distance Measures............................................ 5.5.1 Entropy-Based Measures.........................................
5.5.1.1 Kullback-Leibler Divergence................. 5.5.1.2 Jensen-Shannon Divergence.................... 5.5.2 Bhattacharyya Coefficient..................................... Distancesbetween Sets of Objects .................................... 5.6.1 Jaccard Coefficient.................................................. 5.6.2 Pairwise Distances.................................................. 5.6.2.1 Hausdorff Distance.................................... Earth Mover’s Distance..................................................... 5.7.1 Generalized Earth Mover’sDistance.................... 5.7.2 Match Distance........................................................ Edit Distance ..................................................................... 5.8.1 Hamming Distance.................................................. 5.8.2 Generalized Edit Distance...................................... Distance-Based Structures 6.1 6.2 Triangular Inequality ........................................................ 6.1.1 Indexing Using TriangularInequality.................... VP-Tree .............................................................................. 6.2.1 Structure................................................................. 6.2.2 Bounds..................................................................... Contents 83 83 85 86 87 88 88 89 89 90 91 6.3 6.4 93 95 95 96 96 97 97 98 99 99 99 100 100 101 101 101 102 102 104 105 106 107 108 111 Ill 112 113 113 114 6.5 6.6 6.7 6.8 6.9 xiii 6.2.3 Searching.................................................................. 115 6.2.4
Choosing Vantage Points ...................................... 115 6.2.5 Discussion.................................................................. 115 6.2.6 VPs-Tree.................................................................. 115 6.2.7 VPSB-Tree ............................................................... 116 GH-Tree .............................................................................. 116 6.3.1 Structure.................................................................. 116 6.3.2 Bounds..................................................................... 117 6.3.3 Searching.................................................................. 118 6.3.4 Discussion.................................................................. 118 GNAT ................................................................................. 118 6.4.1 Structure.................................................................. 118 6.4.2 Similarity Searching............................................... 119 6.4.3 Choosing Split Points............................................ 120 M-Tree ................................................................................. 120 6.5.1 Structure.................................................................. 120 6.5.2 Bounds..................................................................... 121 6.5.3 Similarity Search..................................................... 121 6.5.4 Insertion..................................................................... 122 6.5.5
Splitting..................................................................... 123 6.5.6 Split Policies............................................................ 123 6.5.6.1 Choosing Routing Objects................... 123 6.5.6.2 Distributionof Non-Routing Objects . 124 6.5.7 Deletion..................................................................... 124 SA-Tree................................................................................. 125 6.6.1 Optimal Graph........................................................ 125 6.6.2 Structure and Construction................................... 126 6.6.3 Exact Searching ..................................................... 128 6.6.4 Similarity Searching............................................... 128 AESA.................................................................................... 129 6.7.1 Querying .................................................................. 130 6.7.2 Discussion.................................................................. 132 Linear AESA (LAESA) ..................................................... 133 6.8.1 Pivots........................................................................ 133 6.8.2 Choosing Pivots ..................................................... 135 6.8.3 Discussion.................................................................. 135 AESA for Vector Spaces .................................................. 136 6.9.1 Choosing Anchor Points......................................... 136 6.9.2 Discussion..................................................................
136
V Contents Contents XIV High-Dimensional Spaces 139 8.6 7 Curse of Dimensionality 141 7.1 141 141 141 142 143 144 145 146 147 147 148 148 7.2 7.3 7.4 8 Analysis of Search for High-Dimensional Data ............ 7.1.1 Volume at the Boundary....................................... 7.1.2 Range of a Query................................................... 7.1.3 Number of Data Points ....................................... Expected Nearest Neighbor Distance ........................... 7.2.1 Effectiveness of Distance....................................... Expected Number of Page Accesses .............................. 7.3.1 Space-Partitioning Structures.............................. 7.3.2 Data-Partitioning Structures: Hyp er-Rect angles . 7.3.3 Data-Partitioning Structures: Hyper-Spheres . . 7.3.4 Arbitrary Structures............................................. Curse of Dimensionality................................................... High-Dimensionality Structures 149 8.1 149 150 151 152 153 153 154 155 156 156 158 158 159 159 161 164 164 165 166 167 168 168 169 169 171 171 X-Tree .............................................................................. 8.1.1 Overlap.................................................................. 8.1.2 Structure............................................................... 8.1.3 Splitting.................................................................. 8.1.3.1 Overlap Threshold................................. 8.1.4 Insertion, Deletion and Searching........................ 8.2 Pyramid Technique
......................................................... 8.2.1 Locational Code................................................... 8.2.2 Filter-and-Reffne Paradigm................................. 8.2.3 Searching............................................................... 8.2.4 Discussion............................................................... 8.2.5 Extended Pyramid Technique.............................. 8.3 IMinMax ........................................................................... 8.3.1 Mapping.................................................................. 8.3.2 Searching............................................................... 8.3.3 Discussion............................................................... 8.4 VA-File.............................................................................. 8.4.1 Analysis.................................................................. 8.4.2 Searching............................................................... 8.4.3 Utility of VA-File................................................... 8.4.4 Discussion............................................................... 8.4.5 VA+-File............................................................... 8.5 A-Tree .............................................................................. 8.5.1 Virtual Bounding Rectangle................................. 8.5.2 Structure............................................................... 8.5.3 Searching............................................................... VI 8.5.4
Discussion............................................................... IQ-Tree............................................................................. 8.6.1 Structure............................................................... 8.6.2 Searching............................................................... 8.6.3 Construction......................................................... 8.6.4 Level of Quantization.......................................... Data Reduction Techniques 9 Dimensionality Reduction Techniques 9.1 9.2 Properties Useful for Similarity Search ........................ Quality Measures ............................................................ 9.2.1 Distortion............................................................... 9.2.2 Stress..................................................................... 9.3 Embedding........................................................................ 9.4 Singular Value Decomposition (SVD) ........................... 9.4.1 Spectral Decomposition....................................... 9.4.2 Transformation Using SVD................................. 9.4.3 Dimensionality Reduction UsingSVD................. 9.4.4 Dimensionality of Reduced Space........................ 9.5 Principal Component Analysis (PCA)........................... 9.5.1 Algorithm............................................................... 9.5.2 Dimensionality Reduction UsingPCA................. 9.5.3 Number of Reduced Dimensions ........................ 9.6 Multi-Dimensional Scaling (MDS) ................................. 9.6.1
Variants.................................................................. 9.6.2 Sammon Projection ............................................. 9.7 IsoMap .............................................................................. 9.8 FastMap ........................................................................... 9.8.1 Axis with Largest Range....................................... 9.8.2 Projection............................................................... 9.8.3 Subsequent Dimensions....................................... 9.8.4 Discussion............................................................... 9.9 Embedding Methods......................................................... 9.9.1 Lipschitz Embeddings.......................................... 9.9.2 LLR Embedding................................................... 9.9.3 SparseMap ............................................................ 9.9.4 JL Lemma ............................................................ 9.9.4.1 Efficient Construction........................... 9.9.5 Locally Linear Embedding(LLE).......................... 9.10 Bounds on Distortion ...................................................... xv Ill 172 172 173 173 174 175 177 177 178 178 179 180 181 182 182 184 185 186 186 188 188 189 189 190 190 191 191 192 192 195 195 195 196 197 198 198 199 200
Contents Contents XVI 10 Data Representation Techniques 10.1 Discrete Fourier Transform (DFT)..................................... 10.1.1 Properties.................................................................. 10.1.2 Coefficients.............................................................. 10.1.3 Dimensionality Reduction..................................... 10.2 Discrete Cosine Transform (DCT) .................................. 10.3 Discrete Wavelet Transform (DWT) ............................... 10.3.1 Wavelets..................................................................... 10.3.2 Discrete Wavelets..................................................... 10.3.3 Haar Wavelets ........................................................ 10.3.4 Haar Wavelet Functions......................................... 10.3.5 Basis Functions for HaarWavelets....................... 10.3.6 Dimensionality Reduction..................................... 10.3.7 Discussion.................................................................. 10.4 V-Optimal Histogram........................................................ 10.4.1 Optimal Partitioning............................................... 10.4.2 Algorithm.................................................................. 10.4.3 Discussion.................................................................. 201 201 202 202 203 203 204 204 205 205 207 207 208 208 209 209 210 213 Appendices 215 A Memory and Disk Accesses 217 A.l A.2 Memory Access ................................................................ Disks
................................................................................... A.2.1 Disk Capacity.......................................................... A.2.2 Disk Access............................................................. A.2.2.1 Random I/O............................................ A.2.2.2 Sequential I/O......................................... A.3 Flash ................................................................................... В Distances of Bounding Boxes B.l B.2 B.3 B.4 B.5 Distance of a Distance of a Distance of a Distance of a Distance of a Point from a Rectangle ........................... Point from a Sphere ................................. Sphere from a Rectangle........................... Sphere from a Sphere .............................. Rectangle from a Rectangle.................... C Vectors and Matrices C.l C.2 C.3 Vector Spaces ................................................................... Matrices ............................................................................. Properties of Matrices....................................................... C.3.1 Rank of a Matrix.................................................... C.3.2 Eigenvectors and Eigenvalues.............................. C.4 Dimensionality................................................................... 217 218 219 219 219 220 221 223 223 224 224 225 225 227 227 227 228 228 228 229 D Probability and Statistics D.l Random Variable .............................................................. D.2 Probability
Distribution..................................................... D.3 Statistical Parameters........................................................ xvii 231 231 231 232 Bibliography 235 Index 247
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| spelling | Bhattacharya, Arnab Verfasser aut Fundamentals of database indexing and searching 1. issued in paperback Boca Raton CRC Press 2016 xxxi, 252 Seiten Illustrationen, Diagramme 24 cm txt rdacontent n rdamedia nc rdacarrier Indexierung Inhaltserschließung (DE-588)4120478-5 gnd rswk-swf Datenbank (DE-588)4011119-2 gnd rswk-swf File organization (Computer science) Database management Querying (Computer science) Database searching Indexing Datenbank (DE-588)4011119-2 s Indexierung Inhaltserschließung (DE-588)4120478-5 s DE-604 Digitalisierung UB Passau - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=031447610&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Bhattacharya, Arnab Fundamentals of database indexing and searching Indexierung Inhaltserschließung (DE-588)4120478-5 gnd Datenbank (DE-588)4011119-2 gnd |
| subject_GND | (DE-588)4120478-5 (DE-588)4011119-2 |
| title | Fundamentals of database indexing and searching |
| title_auth | Fundamentals of database indexing and searching |
| title_exact_search | Fundamentals of database indexing and searching |
| title_full | Fundamentals of database indexing and searching |
| title_fullStr | Fundamentals of database indexing and searching |
| title_full_unstemmed | Fundamentals of database indexing and searching |
| title_short | Fundamentals of database indexing and searching |
| title_sort | fundamentals of database indexing and searching |
| topic | Indexierung Inhaltserschließung (DE-588)4120478-5 gnd Datenbank (DE-588)4011119-2 gnd |
| topic_facet | Indexierung Inhaltserschließung Datenbank |
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