Ontology-Based Link Weighting for Intelligence Analysis
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Solution Overview
Problem
Identifying and evaluating derived links between concepts in large and complex data sets is challenging, especially when these links are not explicitly stated, posing difficulties in intelligence analysis tasks across various domains such as law enforcement, commercial security, and national security.
Innovation Solution
A method that utilizes an ontology to receive object types and semantic feature types, maps instance information into an ontological form, and applies machine learning to analyze semantic features and patterns, determining weightings for links between objects, thereby automatically generating and prioritizing relevant links.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated mechanisms are used to search through large sets of content sources, then information retrieval efficiency is improved, but the system becomes overwhelmed by the volume of information and cannot effectively identify relevant links
Solution Approach 1:
The patent introduces an intermediary layer consisting of an ontology and semantic pattern matching system between the raw content sources and the search query processing. This intermediary structures the unstructured information into standardized semantic representations, enabling efficient automated search without overwhelming the system. The ontology acts as a mediator that transforms complex unstructured data into organized semantic forms that can be systematically processed.
2Measurement precision
If semantic pattern matching is applied to identify derived links between objects, then link identification accuracy is improved, but the analysis time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-defining ontologies and semantic patterns before the actual link identification process. The ontology and semantic feature types are established in advance, creating a ready-made framework for matching. This preliminary structuring allows the system to quickly match instance information against predefined patterns without performing complex analysis during the actual search, thereby maintaining high accuracy while reducing analysis time.
3Adaptability or versatility
If instance information is mapped into ontological form with detailed semantic features, then semantic analysis capability is improved, but data processing complexity increases
Solution Approach 1:
The patent applies local quality by selectively mapping only the relevant semantic features of instance information into the ontological form, rather than attempting to capture all possible attributes. The system identifies and extracts specific semantic feature types that are pertinent to the analysis task, transforming only those portions of the data that require detailed semantic processing. This selective approach maintains high semantic analysis capability while avoiding the complexity of processing all possible data attributes.
Data Source
AI summary
A system, method, computer program product and computer program for evaluating links between objects are provided. A receive ontology component receives an ontology and an identify component identifies, from the ontology, semantic feature types within the ontology that can be used to measure the links between the objects. A data receive component receives instance information and maps the instance information into an ontological form of the instance information. An analyze component analyzes the ontological form to generate an ontological mapping of the instance information. A match component analyzes the mapping to identify matches with semantic patterns. A strength component analyzes the associated semantic features associated with the objects of the matches to determine weightings for the links of the matches. An alert component provides the links and associated weightings.