
Graph-based Knowledge Representation
Computational Foundations of Conceptual Graphs
By: Marie-Laure Mugnier, Michel Chein
Hardcover | 21 October 2008
At a Glance
444 Pages
16.5 x 24.1 x 3.3
Hardcover
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Industry Reviews
From the reviews:
"This well-written book is a wonderful text for researchers working on theoretical artificial intelligence (AI). Fundamentally, AI represents knowledge with mathematical objects and then designs computational rules to manipulate these objects. ... In summary, this is a theoretical book for a graph-based approach to knowledge representation. ... A number of detailed algorithms presented in the book may serve as good references for designing a variety of AI systems, such as database mining and logic reasoning." (Hsun-Hsien Chang, ACM Computing Reviews, April, 2009)
| Introduction | p. 1 |
| Knowledge Representation and Reasoning | p. 1 |
| Knowledge-Based Systems | p. 2 |
| Requirements for a Knowledge Representation Formalism | p. 3 |
| Conceptual Graphs | p. 8 |
| Basic Notions | p. 8 |
| Subsumption and Homomorphism | p. 9 |
| Formal Semantics | p. 11 |
| Full CGs | p. 12 |
| A Graph-Based Approach to KR | p. 13 |
| Motivations | p. 13 |
| Extensions of the Basic Formalism | p. 14 |
| Several Approaches to CGs | p. 16 |
| Foundations: Basic and Simple Conceptual Graphs | |
| Basic Conceptual Graphs | p. 21 |
| Definition of Basic Conceptual Graphs (BGs) | p. 22 |
| Vocabulary | p. 22 |
| Basic Conceptual Graphs | p. 25 |
| Sub BGs and Pseudo BGs | p. 29 |
| BG Homomorphism | p. 30 |
| Subsumption and Homomorphism | p. 30 |
| Bijective Homomorphisms and Isomorphisms | p. 33 |
| BG Queries and Answers | p. 34 |
| BG Subsumption Properties | p. 35 |
| Subsumption Preorder | p. 35 |
| Irredundant BGs | p. 37 |
| Generalization and Specialization Operations | p. 40 |
| Elementary Generalization Operations for BGs | p. 40 |
| Generalization and Homomorphism | p. 42 |
| Elementary Specialization Operations | p. 45 |
| Specialization and Homomorphism | p. 48 |
| Normal BGs | p. 49 |
| Definition of Normal BGs | p. 49 |
| Elementary Operations for Normal BGs | p. 52 |
| Complexity of Basic Problems | p. 54 |
| Bibliographic Notes | p. 56 |
| Simple Conceptual Graphs | p. 59 |
| Introduction | p. 60 |
| Vocabulary | p. 62 |
| Simple Conceptual Graphs (SGs) | p. 66 |
| Generalization and Specialization Operations | p. 69 |
| Standard and Normal SGs | p. 71 |
| Coref-Homomorphism | p. 72 |
| Antinormal Form and Homomorphism | p. 76 |
| Bibliographic Notes | p. 80 |
| Formal Semantics of SGs | p. 83 |
| Model Semantic | p. 84 |
| Models of SGs | p. 84 |
| Soundness and Completeness of (coref) Homomorphism | p. 87 |
| Logical Semantic | p. 89 |
| The FOL Semantic &Phi | p. 89 |
| Model Semantic and ¿ | p. 91 |
| Positive, Conjunctive, and Existential Fragment of FOL | p. 92 |
| Ordered Language and <$>{\cal L}<$>-Substitution | p. 93 |
| Soundness and Completeness Revisited | p. 94 |
| Relationships Between SGs and FOL(<$>\Lambda, \forall<$>) | p. 95 |
| Another FOL Semantic: ¿ | p. 98 |
| Note on the Relationships Between Description Logics and Conceptual Graphs | p. 100 |
| Bibliographic Notes | p. 104 |
| BG Homomorphism and Equivalent Notions | p. 105 |
| Conceptual Graphs and Conceptual Hypergraphs | p. 107 |
| Conceptual Hypergraphs | p. 107 |
| Different Kinds of Vocabularies | p. 110 |
| Graphs | p. 113 |
| From Graphs to BGs | p. 114 |
| From BGs to Graphs | p. 117 |
| Relational Structures and Databases | p. 119 |
| Relational Structures and BGs | p. 119 |
| Conjunctive Queries and BGs | p. 120 |
| Constraint Satisfaction Problem | p. 124 |
| Definition of CSP | p. 124 |
| From CSP to BGs | p. 127 |
| From BGs to CSP | p. 128 |
| Bibliographic Notes | p. 132 |
| Computational Aspects of Basic Conceptual Graphs | |
| Basic Algorithms for BG Homomorphism | p. 135 |
| Algorithms for BG Homomorphisms | p. 135 |
| Basic Backtrack Algorithms | p. 136 |
| Backtrack Improvements | p. 141 |
| Constraint Processing | p. 151 |
| A Panorama of Constraint Processing Techniques | p. 151 |
| Arc-Consistency | p. 154 |
| Forward Checking | p. 159 |
| Label Comparison | p. 161 |
| Basic Data Structures and Algorithms | p. 163 |
| Related Problems | p. 164 |
| Tree Orders | p. 166 |
| Partition in Chains | p. 167 |
| Lattices | p. 168 |
| Bibliographic Notes | p. 169 |
| Tractable Cases | p. 171 |
| Introduction | p. 171 |
| About Tractability | p. 172 |
| The Structure of the Target BG is of No Help | p. 172 |
| Tractability Based on the Multigraph-Acyclicity of the Source BG | p. 174 |
| Acyclic Multigraphs and Trees | p. 174 |
| BGs Trivially Logically Equivalent to Acyclic BGs | p. 184 |
| Tractability Based on the Hypergraph-Acyclicity of the Source BG | p. 185 |
| Use of a Join Tree | p. 187 |
| Construction of a Join Tree | p. 191 |
| Equivalence with the Existential Conjunctive Guarded Fragment | p. 193 |
| Generalizations of Graph-Acyclicity and Hypergraph-Acyclicity | p. 198 |
| Graphs and Treewidth | p. 198 |
| Hypergraphs and Hypertreewidth | p. 200 |
| Expressivity Results | p. 201 |
| What About Labels? | p. 202 |
| Complementary Notes | p. 204 |
| Other Specialization/Generalization Operations | p. 207 |
| The Least Generalization and Greatest Specialization of Two BGs | p. 208 |
| Basic Compatibility Notions and Maximal Joins | p. 212 |
| Compatible Node Set | p. 212 |
| Maximal Join | p. 215 |
| Compatible Partitions and Extended Join | p. 222 |
| Compatible C-Partition and R-Partition | p. 222 |
| Extended Join | p. 226 |
| Join According to a Compatible Pair of C-Partitions | p. 226 |
| <$>{\cal G}<$>-Specializations | p. 228 |
| Surjective Homomorphism | p. 228 |
| Union | p. 229 |
| Inductive Definition of BGs | p. 231 |
| G-Specializations | p. 232 |
| Type Expansion and Contraction | p. 235 |
| Bibliographic Notes | p. 242 |
| Extensions | |
| Nested Conceptual Graphs | p. 247 |
| Introduction | p. 248 |
| Nested Basic Graphs (NBGs) | p. 249 |
| Nested Graphs (NGs) | p. 256 |
| Nested Typed Graphs | p. 258 |
| The Semantics ¿N | p. 262 |
| Definition of ¿N | p. 263 |
| Soundness and Completeness | p. 265 |
| Representation of Nested Typed Graphs by BGs | p. 267 |
| Bibliographic Notes | p. 270 |
| Rules | p. 273 |
| Definition and Logical Semantics of a Rule | p. 273 |
| Logical Semantics of a Rule | p. 276 |
| Rule as a Bicolored Graph | p. 277 |
| Forward Chaining | p. 278 |
| Rule Application | p. 279 |
| Derivation and Deduction | p. 281 |
| Non-Redundant Rule Application | p. 284 |
| Soundness and Completeness of Forward Chaining | p. 286 |
| Backward Chaining | p. 291 |
| Outline of the Backward Chaining Mechanism | p. 292 |
| Piece Resolution | p. 294 |
| Soundness and Completeness of Backward Chaining | p. 298 |
| Computational Complexity of <$>{\cal FR}<$>-Deducation with Rules | p. 301 |
| Semi-Decidability of <$>{\cal FR}<$>-Deduction with Rules | p. 301 |
| Decidable Cases | p. 303 |
| Bibliographic Notes | p. 307 |
| The BG Family: Facts, Rules and Constraints | p. 311 |
| Overview of the BG Family | p. 311 |
| <$>{\cal FC}<$>: Facts and Constraints | p. 313 |
| Positive and Negative Constraints | p. 313 |
| Translation to FOL | p. 316 |
| Complexity of Consistency and Deduction | p. 318 |
| Combining Rules and Constraints | p. 321 |
| <$>{\cal FRC}<$>: Constraints and Inference Rules | p. 321 |
| <$>{\cal FEC}<$>: Constraints and Evolution Rules | p. 325 |
| <$>{\cal FREC}<$>: Constraints, Inference and Evolution Rules | p. 326 |
| Complexity of Combining Rules and Constraints | p. 326 |
| Complexity in <$>{\cal FRCIFECIFREC}<$> for Particular Cases of Rules and Constraints | p. 327 |
| Particular Cases of Rules | p. 327 |
| Particular Cases of Constraints | p. 330 |
| Bibliographic Notes | p. 334 |
| Conceptual Graphs with Negation | p. 337 |
| Full Conceptual Graphs | p. 338 |
| Existential Graphs: a Diagrammatical System for Logics | p. 338 |
| Full Conceptual Graphs (FCGs) | p. 340 |
| Logical Semantics of FCGs | p. 342 |
| Equivalence of CGs and FOL | p. 344 |
| FCG Calculus | p. 346 |
| Dau' sFCGs | p. 347 |
| Kerdiles' FCGs | p. 348 |
| Conceptual Graphs with Atomic Negation | p. 350 |
| Polarized Graphs | p. 350 |
| Handling Coreference and Difference | p. 355 |
| PG-Deduction and Equivalent Problems | p. 359 |
| Complexity of PG-Deduction | p. 360 |
| Special Cases with Lower Complexity for PG-DEDUCTION | p. 362 |
| Algorithmic Improvements | p. 367 |
| Querying Polarized Graphs | p. 371 |
| Note on Negation and Rules | p. 374 |
| Bibliographic Notes | p. 375 |
| An Application of Nested Typed Graphs: Semantic Annotation Bases | p. 377 |
| Annotation | p. 377 |
| Annotations, Metadata and Resources | p. 377 |
| Examples of Annotation Base Uses | p. 378 |
| Components of an Annotation System | p. 380 |
| Annotation Base | p. 381 |
| Exact Knowledge | p. 382 |
| Modules | p. 383 |
| Plausible Knowledge | p. 384 |
| Querying an Annotation Base | p. 385 |
| Exact Search | p. 386 |
| Approximate Search | p. 386 |
| Annotation and the Semantic Web | p. 388 |
| Conclusion | p. 390 |
| Mathematical Background | p. 393 |
| Sets and Relations | p. 394 |
| Sets and Elements | p. 394 |
| Relations and Mappings | p. 395 |
| Graphs | p. 397 |
| Directed Graphs | p. 397 |
| Homomorphism | p. 399 |
| Different Sorts of Graphs | p. 400 |
| Hypergraphs | p. 403 |
| Ordered Sets | p. 403 |
| Basic Notions | p. 403 |
| Lattices | p. 405 |
| First Order Logic(FOL) | p. 406 |
| Syntax | p. 406 |
| Semantics and Models | p. 408 |
| Clausal Form | p. 409 |
| Resolution and SLD-Resolution | p. 409 |
| Algorithm and Problem Complexity | p. 410 |
| References | p. 413 |
| Index | p. 423 |
| Table of Contents provided by Publisher. All Rights Reserved. |
ISBN: 9781848002852
ISBN-10: 1848002858
Series: Advanced Information and Knowledge Processing
Published: 21st October 2008
Format: Hardcover
Language: English
Number of Pages: 444
Audience: Professional and Scholarly
Publisher: Springer Nature B.V.
Country of Publication: GB
Dimensions (cm): 16.5 x 24.1 x 3.3
Weight (kg): 0.79
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This product is categorised by
- Non-FictionMathematicsCombinatorics & Graph Theory
- Non-FictionReference, Information & Interdisciplinary SubjectsResearch & InformationInformation theory
- Non-FictionComputing & I.T.DatabasesData Mining
- Non-FictionComputing & I.T.Computer ScienceArtificial Intelligence
- Non-FictionMathematicsDiscrete Mathematics

























