"Introduction to constraint databases" - Information and Links:

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with 112 illustrations

"Introduction to constraint databases" was published by Springer in 2002 - New York, it has 393 pages and the language of the book is English.


“Introduction to constraint databases” Metadata:

  • Title: ➤  Introduction to constraint databases
  • Author:
  • Language: English
  • Number of Pages: 393
  • Publisher: Springer
  • Publish Date:
  • Publish Location: New York

“Introduction to constraint databases” Subjects and Themes:

Edition Specifications:

  • Pagination: xiv, 393 p. :

Edition Identifiers:

AI-generated Review of “Introduction to constraint databases”:


"Introduction to constraint databases" Table Of Contents:

  • 1- Machine generated contents note: 1 Infinite Relational Databases 1
  • 2- 1.1 The ViewLevel1
  • 3- 1.2 TheLogical Level4
  • 4- 1.3 Abstract Data Types8
  • 5- 2 Constraint Databases 11
  • 6- 2.1 Constraints11
  • 7- 2.2 The Constraint Data Model20
  • 8- 2.3 Data Abstraction23
  • 9- 3 Relational Algebra and SQL 26
  • 10- 3.1 Relational Algebra26
  • 11- 3.2 SQL34
  • 12- 4 Datalog Queries 40
  • 13- 4.1 Syntax40
  • 14- 4.2 Datalog with Sets45
  • 15- 4.3 Datalog with Boolean Constraints46
  • 16- 4.4 Datalog with Abstract Data Types46
  • 17- 4.5 Semantics48
  • 18- 4.6 Recursive Datalog Queries53
  • 19- 5 Aggregation and Negation Queries 56
  • 20- 5.1 Set Grouping56
  • 21- 5.2 Average, Count, Sum57
  • 22- 5.3 Area and Volume57
  • 23- 5.4 Minimum and Maximum58
  • 24- 5.5 Negation59
  • 25- 5.6 Stratified Datalog Queries59
  • 26- 6 Constraint Automata 62
  • 27- 6.1 Definition of Cnastraint Automata62
  • 28- 6.2 Simplifications of Constraint Automata68
  • 29- 6.3 Analysis of Reachable Configurations73
  • 30- 7 Refinement Queries 79
  • 31- 7.1 The Universal Object Relation Data Model79
  • 32- 7.2 Closed, Open, and Possible Worlds 80
  • 33- 7.3 Syntax82
  • 34- 7.4 Semantics86
  • 35- 7.5 Projection Queries91
  • 36- 7.6 Evaluation of Refinement Queries92
  • 37- 8 Sate Query Languages 97
  • 38- 8.1 SafetyLevels97
  • 39- 8.2 Restriction99
  • 40- 8.3 Safe Aggregation and Negaton Queries 101
  • 41- 8.4 Safe Refinement and Projection Queries101
  • 42- 9 Evaluation of Queries 104
  • 43- 9.1 QuantifierEliminationandSatisfiability105
  • 44- 9.2 Evaluation of Relational Algebra Queries116
  • 45- 9.3 Evaluation of SQL Queries119
  • 46- 9.4 Evaluation of Datalog Queries120
  • 47- 10 Computational Complexity 132
  • 48- 10.1 Complexity Classes and Measures132
  • 49- 10.2 Complexity of Relational Algebra133
  • 50- 10.3 Complexity of Datalog147
  • 51- 10.4 Complexity of Stratified Datalog156
  • 52- 11 Certification 159
  • 53- 11.1 Constant Propagation159
  • 54- 11.2 Variable Independence160
  • 55- 11.3 Monotonicity160
  • 56- 11.4 Acyclicity 161
  • 57- 11.5 Tightening Bounds161
  • 58- 11.6 Tightening Coefficients161
  • 59- 11.7 VectorAdditionSystem162
  • 60- 11.8 Positive Stochastic Matrix Multiplication164
  • 61- 12 Implementation Methods 168
  • 62- 12.1 Evaluation with Gap-Graphs 168
  • 63- 12.2 Evaluation with Matrices174
  • 64- 12.3 Boolean Constraints182
  • 65- 12.4 Optimization of Relational Algebra186
  • 66- 13 Spatiotemporal Databases 195
  • 67- 13.1 Extreme Point Data Models196
  • 68- 13.2 Parametric Extreme Point Data Models198
  • 69- 13.3 Geometric Transformation Data Models206
  • 70- 13.4 Queries208
  • 71- 14 Interoperability 219
  • 72- 14.1 DataInteroperability219
  • 73- 14.2 Query Interoperability235
  • 74- 14.3 Other Types of Interoperability242
  • 75- 15 Approximation by Constraints 246
  • 76- 15.1 Triangulated Irregular Networks247
  • 77- 15.2 Piecewise Linear Approximation of Tune Series 250
  • 78- 15.3 Parametric Triangulated Irregular Networks263
  • 79- 15.4 Parametric Rectangles Appioximation of Raster Movies265
  • 80- 16 Data Visualization 270
  • 81- 16.1 Isometric Color Bands270
  • 82- 16.2 Value-by-Area Cartogram274
  • 83- 16.3 Animation of Moving Objects280
  • 84- 17 Indexing 286
  • 85- 17.1 Minimum Bounding Parametric Rectangles287
  • 86- 17.2 The Parametric R-Tree Index Structure292
  • 87- 17.3 Indexing Constraint Databases298
  • 88- 18 The MLPQ System 302
  • 89- 18.1 The MLPQ Database System Architecture302
  • 90- 18.2 MLPQ Input Files304
  • 91- 18.3 The MLPQ Graphical User Interface307
  • 92- 18.4 Recursive Queries314
  • 93- 19 The DISCO System 319
  • 94- 19.1 DISCO Queries319
  • 95- 19.2 Implementation323
  • 96- 19.3 Using the DISCO System329
  • 97- 19.4 Extensibility of the DISCO System330
  • 98- 20 The PReSTO ystem 332
  • 99- 20.1 PReSTO Input Files332
  • 100- 20.2 The PReSTO Graphical Use Ierface335
  • 101- 20.3 Implementation338
  • 102- 21 Computer Vision ' 343
  • 103- 21.1 Affine Inariance 344
  • 104- 21.2 Affine-nvariant Similarity Measures346
  • 105- 21.3 The Color Ratios Similarity Measure347
  • 106- 22 Bioinformaties 351
  • 107- 22.1 The Genome Map Assembly Problem351
  • 108- 22.2 The Big-Bag Matching Problem352
  • 109- 22.3 AConstraint-AutomataSolution353
  • 110- 23 Environmental Modeling 361
  • 111- 23.1 Preditive Spread ModejinF36?
  • 112- 23.2 Visualization366
  • 113- 23.3 A Deision Suport System366
  • 114- Bibliography 370
  • 115- Index 390.

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