AI Question Answer Pair Generation for IT Event Analysis
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Solution Overview
Problem
Traditional IT management solutions struggle to intelligently sort significant events from large volumes of data across dynamic IT environments, fail to correlate data across different environments, and cannot provide real-time insight and predictive analysis quickly enough to meet user expectations.
Innovation Solution
An AI-powered system that uses machine learning to automatically generate and rank question-answer pairs from source documents, enabling intelligent data analysis, event identification, and rapid issue resolution by parsing input documents, extracting key concepts, generating questions, and ranking QA pairs for quick user access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional IT management solutions are used to process large volumes of data, then data processing capacity is maintained, but the ability to intelligently sort significant events and provide real-time insight deteriorates
Solution Approach 1:
The patent replaces traditional mechanical data processing systems with an AI-based natural language generation system. The system uses machine learning models to automatically generate human-readable summaries of significant events from raw data, transforming the mechanical processing approach into an intelligent synthesis approach that can identify and communicate important information without manual intervention.
Solution Approach 2:
The system enables self-service by automatically generating event summaries and insights without requiring human analysts to manually process data. The AI model autonomously identifies significant events, extracts key information, and produces readable summaries, allowing the system to serve itself in the information synthesis task rather than relying on human operators.
2Adaptability or versatility
If traditional IT management solutions are used, then system simplicity is maintained, but the ability to correlate data across different environments deteriorates
Solution Approach 1:
The patent implements a universal AI-based natural language generation system that can process and summarize data from multiple different IT environments and data sources. The system is designed to handle diverse input types and generate consistent event summaries across different platforms, making it adaptable to various environments without requiring environment-specific processing logic.
3Measurement precision
If manual event sorting is performed, then processing accuracy is maintained, but response time to identify significant events deteriorates
Solution Approach 1:
The patent replaces manual event sorting with an AI-based natural language generation system that automatically identifies and summarizes significant events. The system uses machine learning models trained to recognize important patterns in data, enabling automated event identification that maintains accuracy while dramatically reducing the time required compared to manual processing.
Data Source
AI summary
A computerized method, system and computer program product for automatically generating question and answer pairs. One embodiment of the method may comprise receiving an input document, the input document comprising content. The method may further comprise generating, by a first machine learning model from the input document, a plurality of answers based on the content of the input document, and generating, by a second machine learning model from the input document, a question for each of the plurality of answers to form a plurality of question-answer pairs. The method may further comprise ranking, by a third machine learning model, the plurality of question-answer pairs, selecting a predetermined number of highest ranked question-answer pairs, and returning the predetermined number of highest ranked question-answer pairs to a user.