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This book illustrates how to use description logic-based formalisms to their full potential in the creation, indexing, and reuse of multimedia semantics. To do so, it introduces researchers to multimedia semantics by providing an in-depth review of state-of-the-art standards, technologies, ontologies, and software tools. It draws attention to the importance of formal grounding in the knowledge representation of multimedia objects, the potential of multimedia reasoning in intelligent multimedia applications, and presents both theoretical discussions and best practices in multimedia ontology engineering. 

Readers already familiar with mathematical logic, Internet, and multimedia fundamentals will learn to develop formally grounded multimedia ontologies, and map concept definitions to high-level descriptors. The core reasoning tasks, reasoning algorithms, and industry-leading reasoners are presented, while scene interpretation via reasoning is also demonstrated.

Overall, this book offers readers an essential introduction to the formal grounding of web ontologies, as well as a comprehensive collection and review of description logics (DLs) from the perspectives of expressivity and reasoning complexity. It covers best practices for developing multimedia ontologies with formal grounding to guarantee decidability and obtain the desired level of expressivity while maximizing the reasoning potential. The capabilities of such multimedia ontologies are demonstrated by DL implementations with an emphasis on multimedia reasoning applications.

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This book illustrates how to use description logic-based formalisms to their full potential in the creation, indexing, and reuse of multimedia semantics. To do so, it introduces researchers to multimedia semantics by providing an in-depth review of state-of-the-art standards, technologies, ontologies, and software tools. It draws attention to the importance of formal grounding in the knowledge representation of multimedia objects, the potential of multimedia reasoning in intelligent multimedia applications, and presents both theoretical discussions and best practices in multimedia ontology engineering.  

Readers already familiar with mathematical logic, Internet, and multimedia fundamentals will learn to develop formally grounded multimedia ontologies, and map concept definitions to high-level descriptors. The core reasoning tasks, reasoning algorithms, and industry-leading reasoners are presented, while scene interpretation via reasoning is also demonstrated.

Overall, this book offers readers an essential introduction to the formal grounding of web ontologies, as well as a comprehensive collection and review of description logics (DLs) from the perspectives of expressivity and reasoning complexity. It covers best practices for developing multimedia ontologies with formal grounding to guarantee decidability and obtain the desired level of expressivity while maximizing the reasoning potential. The capabilities of such multimedia ontologies are demonstrated by DL implementations with an emphasis on multimedia reasoning applications.

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CONTENTS
1 Multimedia Semantics = 1
 1.1 Rationale = 1
 1.2 Feature Extraction and Feature Statistics for Classification = 3
 1.3 Machine Learning for Multimedia Understanding = 4
 1.4 Object Detection and Recognition = 5
 1.5 Spatiotemporal Data Extraction for Video Event Recognition = 5
 1.6 Conceptualization of Multimedia Contents = 6
 1.7 Concept Mapping = 8
 1.8 Implementation Potential : From Search Engines to Hypervideo Applications = 10
 1.9 Summary = 10
2 Knowledge Representation with Semantic Web Standards = 11
 2.1 The Semantic Web = 11
 2.2 Unstructured, Semistructured, and Structured Data = 12
 2.3 RDF = 14
 2.4 RDFS = 19
 2.5 OWL = 20
  2.5.1 OWL Variants = 21
  2.5.2 Modeling with OWL = 22
  2.5.3 Serialization = 30
 2.6 Simple Knowledge Organization System = 33
 2.7 Rule Languages = 35
  2.7.1 Semantic Web Rule Language = 35
  2.7.2 Rule Interchange Format = 39
 2.8 Structured Data Deployment = 39
  2.8.1 Linked Open Data Datasets = 39
  2.8.2 Graph Databases : Triplestores and Quadstores = 44
  2.8.3 Lightweight Annotations = 45
 2.9 Summary = 49
3 The Semantic Gap = 51
 3.1 Low-Level Descriptors = 51
  3.1.1 Common Visual Descriptors = 52
  3.1.2 Common Audio Descriptors = 53
  3.1.3 Common Spatiotemporal Feature Descriptors, Feature Aggregates, and Feature Statistics = 54
 3.2 The Discrepancy Between Low-Level Features and High-Level Semantics = 55
 3.3 Semantic Enrichment of Multimedia Resources = 57
  3.3.1 Semantic Enrichment of Images = 58
  3.3.2 Structured 3D Model Annotation = 59
  3.3.3 Semantic Enrichment of Audio and Video = 60
 3.4 Summary = 66
4 Description Logics : Formal Foundation for Web Ontology Engineering = 67
 4.1 Description Logics = 67
  4.1.1 Nomenclature = 68
  4.1.2 Annotation and Naming Conventions = 69
  4.1.3 Interpretation = 71
  4.1.4 DL Constructor Syntax and Semantics = 73
  4.1.5 DL Axiom Syntax and Semantics = 75
  4.1.6 TBox, ABox, and RBox = 78
  4.1.7 Relation to Other Logics = 81
 4.2 Description Logic Families = 83
  4.2.1 ALC and the Basic Description Logics = 83
  4.2.2 The EL Family of Description Logics = 84
  4.2.3 The DL-Lite Family of Description Logics = 84
  4.2.4 Frame-Based Description Logics (FL) = 86
  4.2.5 The SH Family of Description Logics = 86
  4.2.6 Spatial Description Logics = 87
  4.2.7 Temporal Description Logics = 91
  4.2.8 Spatiotemporal Description Logics = 102
  4.2.9 Fuzzy Description Logics = 103
 4.3 Extending DL Expressivity = 105
 4.4 Formal Representation of Images = 106
 4.5 Formal Representation of 3D Models and Scenes = 108
 4.6 Formal Representation of Audio = 109
 4.7 Formal Representation of Video Scenes = 112
  4.7.1 Spatial Annotation = 113
  4.7.2 Temporal Annotation = 113
  4.7.3 Spatiotemporal Annotation = 116
 4.8 Summary = 120
5 Multimedia Ontology Engineering = 121
 5.1 Introduction to Ontology Engineering = 121
  5.1.1 Specification = 122
  5.1.2 Knowledge Acquisition = 123
  5.1.3 Conceptualization = 123
  5.1.4 Assessment of Potential Term Reuse = 123
  5.1.5 Enumerating the Terms of the Knowledge Domain = 124
  5.1.6 Building the Concept Hierarchy = 124
  5.1.7 Defining Roles = 125
  5.1.8 Adding Individuals = 126
  5.1.9 Creating a Ruleset = 126
  5.1.10 Evaluation = 126
  5.1.11 Documentation = 127
  5.1.12 Maintenance = 127
 5.2 Ontology Engineering Tools = 128
  5.2.1 Ontology Editors = 128
  5.2.2 Ontology Analysis Tools = 134
 5.3 The Evolution of Multimedia Ontology Engineering = 134
  5.3.1 Semistructured Vocabularies = 135
  5.3.2 Structured Ontologies Mapped from Semistructured Vocabularies = 136
  5.3.3 Structured Multimedia Ontologies = 140
 5.4 Ontology-Based Multimedia Annotation Tools = 143
  5.4.1 Structured Image Annotation Tools = 143
  5.4.2 Structured Audio Annotation Tools = 144
  5.4.3 Structured Video Annotation Tools = 145
  5.4.4 Structured 3D Model Annotation Tools = 148
 5.5 Summary = 149
6 Ontology-Based Multimedia Reasoning = 151
 6.1 Rationale = 151
 6.2 Core Reasoning Tasks = 152
 6.3 Reasoning Rules = 155
  6.3.1 RDFS Reasoning Rules = 155
  6.3.2 Ter Horst Reasoning Rules = 156
  6.3.3 OWL 2 Reasoning Rules = 158
 6.4 DL Reasoning Algorithms = 168
  6.4.1 Tableau-Based Consistency Checking = 169
  6.4.2 Automata = 171
  6.4.3 Resolution = 171
 6.5 Reasoning Complexity = 171
 6.6 DL-Based Reasoners = 173
  6.6.1 HermiT = 174
  6.6.2 Pellet = 175
  6.6.3 FaCT++ = 176
  6.6.4 Racer = 178
 6.7 Image Interpretation = 178
  6.7.1 Image Interpretation as Abduction = 181
  6.7.2 Image Interpretation Using Fuzzy DL Axioms = 183
 6.8 Video Scene Interpretation = 184
  6.8.1 Video Event Recognition via Reasoning over Temporal DL Axioms = 184
 6.9 Distributed and Federated Reasoning = 185
 6.10 Summary = 186
References = 187
Index = 201