Proactive News Analytics Using Custom Keyword Libraries
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Solution Overview
Problem
Current analysis tools fail to effectively extract and process predictive and conditional statements from unstructured sources, leading to difficulties in identifying relevant information in real-time, especially in financial contexts, as they are not customized to individual users and often lose their competitive advantage by the time events occur.
Innovation Solution
A computer-implemented method that extracts predictive statements, normalizes and links them, removes inconsistencies, creates custom keyword libraries, and uses natural language processing to analyze data from various sources, including news and social media, for proactive sentiment analysis and confidence scoring, enabling proactive awareness of predicted events.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If typical analysis tools are used to monitor news sources, then information can be collected, but the tools fail to extract relevant predictive statements and are not customized to individual users
Solution Approach 1:
The system creates customized keyword libraries and natural language processing structures tailored to each user's specific interests and industry. Instead of using generic analysis tools, the system adapts the keyword library and NLP structures to match individual user preferences, ensuring that predictive statements are extracted and monitored according to each user's specific needs and industry context.
Solution Approach 2:
The system extracts and processes predictive statements from research reports in advance, creating customized keyword libraries and NLP structures before the events occur. This preliminary action allows the system to proactively monitor for signs of predicted events rather than reacting after they happen, giving users a competitive advantage by anticipating future developments in their industry.
2Loss of time
If research reports with predictive statements are processed, then future events can be anticipated, but the statements are difficult to process due to conditional formatting and lack of real-time relevance
Solution Approach 1:
The system segments the processing into distinct stages: extracting predictive statements from research reports, normalizing them into a standardized format, creating customized keyword libraries, generating NLP structures, and then monitoring for matching events. This segmentation allows each stage to be optimized independently, making the overall complex process manageable and efficient.
Solution Approach 2:
The system transforms conditional statements from research reports into a standardized normalized format with consistent parameters. By changing the parameter representation of predictive statements into a uniform structure that includes event type, condition, and predicted outcome, the system simplifies processing and enables efficient matching with real-time news data without requiring complex interpretation of various conditional formats.
3Reliability
If predictive statements are monitored until events occur, then relevant information can be found, but the competitive advantage diminishes by the time events happen
Solution Approach 1:
The system extracts and processes predictive statements from research reports in advance, creating customized keyword libraries and NLP structures before the predicted events occur. This allows the system to proactively monitor for signs of predicted events rather than reacting after they happen. By preparing the monitoring infrastructure beforehand and continuously scanning for matching conditions, the system can detect early signs of predicted events and alert users before the events fully unfold, maintaining competitive advantage.
Solution Approach 2:
The system continuously monitors news and social media sources, comparing real-time data against the customized keyword libraries and NLP structures derived from predictive statements. When matching conditions are detected, the system provides feedback to users through customized alerts and analyses. This feedback mechanism enables users to act on predicted events as they unfold, maintaining timely competitive advantage while ensuring information accuracy through continuous verification against the original predictive statements.
Data Source
AI summary
Systems and methods may provide proactive news analytics based on integrated prediction statements. Users may extract and collect conditional statements from research reports. A compiled list based on the processing/linking of statements for signal generation may then be created. Similarly, a list of counter statements that are assigned a conflict rating that specifies how much agreement/disagreement on a specific topic exists for the counter statement and the statement itself may be created. The custom library may have semantic capabilities to justify conditional statements in order to capture meaning and identify supporting news related to the statement. When a relevant event is detected that relates to a conditional statement, expected conclusions are linked, and customized indexes are calculated to allow for analysis of the relevant event.