Intelligence Analysis Using Template-Based Data Aggregation
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Solution Overview
Problem
Current intelligence data analysis is burdensome and often manual, becoming increasingly challenging as the volume of data grows, requiring more efficient methods to analyze persons, groups, and associated objects and locations in real-time.
Innovation Solution
The implementation of a computing system that uses templates to evaluate gathered data, simulating human intelligence analysis by correlating current and historical information to assess potential threats or useful affiliations, and generating hypotheses based on aggregate data sets, with the ability to learn and update knowledge continuously.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual data analysis methods are used, then analysis can be performed with simple tools, but productivity decreases and loss of time increases as data volume grows
Solution Approach 1:
The patent replaces manual mechanical analysis processes with an automated computer-based system that uses templates and algorithms to evaluate data elements, aggregate data sets, and generate intelligence reports automatically, thereby increasing productivity and reducing time loss
Solution Approach 2:
The system enables self-service intelligence analysis by automatically performing data evaluation, hypothesis generation, and report creation without requiring manual intervention at each step, allowing the system to serve its own analytical needs efficiently
2Measurement precision
If more data is gathered to improve analysis accuracy, then measurement precision improves, but device complexity and loss of time increase
Solution Approach 1:
The patent segments the complex data analysis process into distinct template-based evaluation steps, where each template handles specific aspects of data analysis independently, making the overall complex system manageable and efficient
Solution Approach 2:
The patent creates universal templates that can evaluate multiple types of data elements and generate various intelligence products through a single unified system, reducing overall system complexity while maintaining comprehensive analytical capability
3Productivity
If automated analysis is implemented to improve productivity, then loss of time decreases, but manufacturing precision and measurement precision may worsen
Solution Approach 1:
The patent incorporates feedback mechanisms where evaluation results from templates feed into subsequent analysis steps, allowing the system to continuously refine its assessments and improve precision through iterative processing of data elements and hypotheses
Solution Approach 2:
The patent performs preliminary data evaluation and hypothesis generation automatically before final assessment, preparing refined data sets and candidate hypotheses in advance to ensure high precision in the final intelligence products
Data Source
AI summary
A particular method includes receiving a data element at a processor of a computing device and determining whether the received data element is related to a known data set corresponding to one or more known data elements stored in a memory accessible to the processor. The method further includes, when the received data element is related to a particular known data set, forming an aggregate data set by combining the received data element with the particular known data set. The method also includes evaluating one or more analysis templates based on the aggregate data set. Each analysis template corresponds to a different hypothesis. Evaluating the one or more analysis templates results in a determination regarding a probability that a particular hypothesis is true based on the aggregate data set.