| Description |
1 online resource |
| Series |
Artech House Intelligence and Information Operations Series |
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Artech House intelligence and information operations series.
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| Contents |
Data Fusion Support to Activity-Based Intelligence ; Contents; Preface; Acknowledgments; 1 Introduction and Background; References; 2 Foundational Theory; 2.1#First Principles; 2.2#Behavior Understanding ; 2.3#Fusion Forms ; 2.4#Supplemental Fusion Services; 2.4.1#Message Extraction Service; 2.4.2#Message Normalization Service ; 2.4.3#Location Normalization Service; 2.4.4#Temporal Normalization Service; 2.4.5#Filtering Service; 2.4.6#Database Support; 2.4.7#Human-Computer Interaction; 2.4.8#Entity Support Service; 2.4.9#Location Support Service; 2.4.10#Temporal Support Service |
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2.4.11#Context Support Service 2.5#Mapping Fusion Composition Products for Specific Applications; 2.6#Selected Problem Domain Fusion Model; 2.7#Mapping from Composition Products to Functional Operations; 2.7.1#One-to-Many Links; 2.7.2#Many-to-One Links; 2.7.3#Missing Links to a Right-Hand-Side Function; 2.7.4#Right-Hand-Side Functions with no Link from Composition Products; 2.8#Mapping to Different Problem Domain Models ; 2.8.1#Aircraft Flight Safety Domain Model ; 2.8.2#Robotic Vehicle Control Model; 2.9#Context; 2.9.1#Context as Constraints; 2.9.2#Context as Features |
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2.9.3#Constraint Versus Feature2.10#Database Considerations; 2.11#Representation of Semantic Information; 2.11.1#Location and Time; 2.11.2#Location Descriptions Outside Adverbial Phrases; 2.11.3#Semi-Automated Fact Extraction from Unstructured Text; 2.11.4#Example Application; 2.11.5#Semi-Automated Parser Implementation; 2.12#Combining Mixed Hard and Soft Data ; References; 3 Prototype Implementation; 3.1#Location Normalization Service; 3.1.1#Formalism; 3.2#Spatial Reasoning Support Service; 3.3#Temporal Normalization Service ; 3.4#Temporal Reasoning Support Service |
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3.5#Context Support Service3.6#Level 1: Smart Track; 3.7#Level 2: Entity-Entity Relationship Discovery; 3.8#Navigating Large Graphical Data Structures ; 3.9#Second Generation Prototype ; 3.10#Hard-Soft Fusion Example; 4 Higher-Level Reasoning; 4.1#Transitivity; 4.2#Multihypothesis Reasoning ; 4.3#Truth Maintenance; 4.4#Data Mining; 4.5#Reinterpretation of Fusion Forms; 4.5.1#Hypothesis Generation Forms; 4.5.2#Process Control; 4.5.3#Fusion Forms as Control Functions; 4.6#Visualization of Spatial/Temporal Relations in Social Networks; References; 5 Special Functions |
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5.1#High Value Entity (HVE) Discovery5.2#Key Locations; 5.3#Locations of Interest Discovery; 5.4#Alerts; 6 The Way Ahead; 6.1#Preliminary Thoughts; 6.2#Support to Activity-Based Intelligence; 6.3#Level 1 Extensions; 6.4#Level 2 Extensions ; 6.5#Relations; 6.6#Network Analysis ; 6.7#Organization Discovery ; 6.8#Higher-Level Product Abstraction; 6.9#Activity Exploitation; 6.10#Roles and Behavior Understanding; 6.11#User-Directed Tool Development; 6.12#Fact Normalization; 6.13#Event Identification and Exploitation ; References; 7 Refinement Extensions; 7.1#Pedigree-Related Metrics |
| Summary |
This new resource provides a coherent, intuitive, and theoretical foundation for the fusion and exploitation of traditional sensor data as well as text-based information. In addition to presenting a detailed discussion of base-level data fusion requirements, a variety of higher level exploitation algorithms are presented that perform fully automated relationship discovery, rank interest level of entities, and support context-sensitive behavior understanding (both static and dynamic context). This book identifies eight canonical fusion forms as well as twenty foundational fusion services to enable formal mapping between models and services. Normalization and representation processes for (hard) sensor data and (soft) semantic data are described as well as methods for combining hard and soft data.nIncluded is a prototype fusion system developed to implement virtually all the presented applications in order to demonstrate the robustness and utility of the design principles presented in this resource. The prototype system presented supports a variety of user workflows and all the applications are fully integrated. There is extensive fusion system output for unclassified scenarios to permit the reader to fully understand all presented design principles. This book also presents context-sensitive fuzzy semantic spatial and temporal reasoning. Publisher abstract |
| Bibliography |
Includes bibliographical references and index |
| Subject |
Multisensor data fusion.
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Multisensor data fusion
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| Form |
Electronic book
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| ISBN |
9781608078462 |
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1608078469 |
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