Automated Data Collection Utility for Open Source Intelligence
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Solution Overview
Problem
Open source intelligence gathering systems face challenges in efficiently collecting and analyzing vast amounts of publicly available data due to sub-optimal search engine technologies and website source biases, leading to a trade-off between analysis quality and timeliness, with users often receiving irrelevant results.
Innovation Solution
The development of automated, lightweight data collection utilities that extract content of interest from websites by parsing source code, determining heuristic scores, and generating objects for subsequent analysis, along with tools for sentiment analysis, hierarchical signature creation, and information flow network inference to provide actionable intelligence.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If automated data collection systems collect vast amounts of open source data, then the quantity of available information increases, but the quality and relevance of analyzed results deteriorates due to sub-optimal search engine technologies and website source biases
Solution Approach 1:
The patent extracts and removes harmful or irrelevant elements from webpages (such as advertisements, navigation elements, and bias-prone content) to isolate the valuable intelligence data. This extraction process purifies the collected data, maintaining high quantity while improving quality by eliminating noise and biases.
Solution Approach 2:
The system applies different processing and weighting to different portions of collected data based on their relevance and reliability. By assigning local quality metrics to different data sources and content types, the system can prioritize high-quality intelligence while still maintaining comprehensive data collection.
2Quantity of substance
If existing systems return thousands of search results to users, then the completeness of information coverage improves, but the ease of operation deteriorates as users must manually determine which results are valuable
Solution Approach 1:
The system incorporates feedback mechanisms that learn from user interactions with search results, automatically adjusting and refining the presentation of results based on what users find valuable. This feedback loop enables the system to maintain comprehensive coverage while progressively improving ease of operation through adaptive filtering.
Solution Approach 2:
The patent implements automated filtering and ranking systems that self-adjust to prioritize relevant results without requiring manual user intervention. The system serves itself by automatically identifying and presenting the most valuable intelligence while filtering out irrelevant content, making the system self-regulating and easier to operate.
3Productivity
If comprehensive automated collection processes are implemented, then the productivity of data gathering increases, but the device complexity increases due to the need for advanced parsing and analysis tools
Solution Approach 1:
The patent divides the complex data collection and analysis system into distinct modular components, each handling specific tasks such as data extraction, parsing, filtering, and analysis. This segmentation allows the system to achieve high productivity through automated processes while managing complexity through modular design, where each component can be independently optimized and maintained.
Data Source
AI summary
Systems and methods (e.g., utilities) for use in providing automated, lightweight collection of online, open source data which may be content-based to reduce website source bias. In one aspect, a utility is disclosed for use in extracting content of interest from at least one website or other online data source (e.g., where the extracted content can be used in a subsequent search query). In other aspects, utilities are disclosed that are operable to perform various types of analyzes on such extracted content and present graphical representations of such analyzes on a display of a client device.