Data fusion support to activity-based intelligence / Richard T. Antony.
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 al...
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| Online Access: |
Full Text (via ProQuest) |
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| Main Author: | |
| Format: | eBook |
| Language: | English |
| Published: |
Boston :
Artech House,
[2016]
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| Series: | Artech House intelligence and information operations series.
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| Subjects: |
Table of 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.
- 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.
- 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.
- 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.
- 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.