Generative AI Issue Monitoring for New Topic Detection
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Solution Overview
Problem
Existing technologies lack efficient methods for monitoring and identifying changes in specific issues related to topics such as persons, products, or events in real-time using generative artificial intelligence, and fail to distinguish between new and related issues effectively.
Innovation Solution
An issue monitoring apparatus and method utilizing a generative artificial intelligence-based language model to analyze input data, generate metadata, determine similarities, and identify new issues by comparing metadata, with features like clustering and question-based data search to enhance information accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual monitoring of issues is performed, then information accuracy can be maintained, but time consumption and labor intensity increase significantly
Solution Approach 1:
The patent replaces manual mechanical monitoring processes with an automated system comprising a data acquisition module, metadata generation module using generative AI, similarity calculation module, and issue determination module. This substitution maintains information accuracy through structured metadata extraction while eliminating time-consuming manual review processes.
Solution Approach 2:
The system enables self-service automated monitoring where the apparatus independently acquires data, generates metadata, calculates similarities, and determines new issues without human intervention. The generative AI model automatically processes information and the system self-manages the complete monitoring workflow, significantly reducing labor intensity while maintaining accuracy through algorithmic consistency.
2Measurement precision
If comprehensive data analysis is performed to identify new issues, then detection accuracy improves, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the complex analysis process into distinct functional modules: data acquisition, metadata generation using generative AI, similarity calculation, and issue determination. Each module handles a specific aspect of the analysis, reducing overall computational complexity while maintaining comprehensive detection accuracy through systematic processing of different data dimensions.
Solution Approach 2:
The patent introduces metadata as an intermediary representation between raw data and final issue determination. The generative AI model creates condensed metadata that captures essential information, serving as a bridge that simplifies subsequent similarity calculations and issue identification while preserving detection accuracy through structured information representation.
3Speed
If real-time issue monitoring is implemented, then responsiveness to new issues improves, but system resource consumption increases
Solution Approach 1:
The patent implements periodic batch processing where the system acquires data, generates metadata, and performs similarity analysis at regular intervals rather than continuously in real-time. This periodic operation maintains responsiveness to new issues by systematically updating at set frequencies while significantly reducing system resource consumption compared to continuous real-time processing.
Data Source
AI summary
Disclosed are an apparatus and a method for performing issue monitoring using a language model based on a generative artificial intelligence. An issue monitoring apparatus according to an exemplary embodiment includes an interface unit which inputs and outputs data with an external device and an analysis unit which analyzes an issue about a specific topic from input data received through the interface unit using a generative artificial intelligence based language model to generate first metadata.