Automated Open Source Intelligence Extraction and Analysis
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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 manual analysis requirements, often returning irrelevant results due to website source biases and extraneous content.
Innovation Solution
The development of automated tools that extract meaningful content from online data sources by parsing source code, assigning heuristic scores to determine relevant content, and providing analytical visualizations for sentiment analysis and trend discovery, allowing for the automated selection of terms for analysis and presentation of results in graphical formats.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If automated collection processes and search engine technologies are used to gather open source intelligence, then the quantity of collected data increases, but the quality and relevance of results deteriorate due to website source biases and extraneous content
Solution Approach 1:
The patent segments web content into distinct elements (navigation, advertisements, article text, etc.) and applies different processing rules to each segment. This allows the system to extract only relevant content while filtering out extraneous material, thereby maintaining data quality while processing large quantities of information.
Solution Approach 2:
The patent extracts specific relevant content from webpages while leaving out irrelevant portions. By identifying and extracting only the meaningful segments (such as article text while excluding navigation and ads), the system improves result relevance without sacrificing the ability to process large data volumes.
2Measurement precision
If manual analysis is performed on collected data to ensure quality, then the precision of intelligence analysis improves, but the productivity and timeliness of intelligence gathering deteriorate
Solution Approach 1:
The patent implements self-service through automated content extraction and analysis systems that perform quality control functions without human intervention. The system automatically identifies, extracts, and analyzes relevant content, maintaining high precision while enabling processing of large data volumes that would be impossible to handle manually.
Solution Approach 2:
The patent replaces manual mechanical analysis with automated computational systems. By substituting human analysts with algorithmic content extraction and analysis tools, the system maintains analytical precision while dramatically increasing productivity and timeliness of intelligence gathering.
3Loss of information
If comprehensive search queries are performed to capture all relevant information, then the completeness of intelligence collection improves, but the quantity of irrelevant results increases due to sub-optimal search engine technologies
Solution Approach 1:
The patent applies local quality by treating different portions of web content differently based on their relevance. Instead of uniformly processing all content, the system identifies and processes only the locally relevant segments (such as article bodies while ignoring navigation menus and advertisements), thereby reducing irrelevant results while maintaining completeness of intelligence collection.
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.