Keyword-Guided AI Summarization With Summary Verification
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Solution Overview
Problem
Existing summary functions in generative AI systems fail to provide customized and accurate summaries that match individual user intentions and organizational requirements, often leading to incorrect results and lack of error verification.
Innovation Solution
A method utilizing generative AI to group user-specified keywords semantically, expand them with relevant terms, and verify summaries against a knowledge repository to ensure accuracy and reliability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a simple summary function is used to process information, then processing speed is improved, but summary accuracy and customization to user needs deteriorates
Solution Approach 1:
The patent introduces an LLM-based summary generation unit as an intermediary between the information processing system and the user. This intermediary component generates customized summaries by processing input information through advanced language models, thereby improving summary accuracy without significantly impacting overall system productivity.
Solution Approach 2:
The system changes the parameters of summary generation by allowing users to specify multiple keywords and adjust summary length. The LLM processes these parameter changes to generate customized summaries that accurately reflect user needs, resolving the contradiction between simple processing and accurate customization.
2Adaptability or versatility
If user-specified keywords are incorporated into summary generation, then summary customization is improved, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-processing user input to extract keywords before passing them to the LLM. This preliminary keyword extraction step simplifies the overall system architecture while maintaining high customization capability, as the LLM receives structured input rather than requiring complex real-time analysis.
3Reliability
If summary verification against knowledge repository is performed, then summary reliability is improved, but processing time increases
Solution Approach 1:
The patent implements a feedback mechanism where generated summaries are verified against a knowledge repository. The verification unit compares summary content with stored knowledge to identify potential errors, providing feedback that improves summary reliability. This feedback loop ensures accuracy while maintaining reasonable processing time through efficient comparison algorithms.
Data Source
AI summary
A method for keyword-based information summarization using generative AI with user-specified keywords, and a device therefor are proposed, wherein a summary focused on information related to keywords specified by a user is provided by utilizing generative AI such as an LLM, so as to enable the user to obtain satisfactory summary information that accurately matches the user's intention and specific situation such as work, and the method includes an input step of receiving summary target information and one or more keywords, which are specified or input from a user, a summary generation step of causing the generative AI to generate and return a summary of the summary target information with content related to the keywords based on the keywords and the summary target information, and a summary output step of providing a final summary to the user based on the summary returned by the generative AI.