Generative AI Technology Analysis Metaframe Structure
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The manual processing of vast amounts of patent data is time-consuming and prone to errors, leading to inconsistent and subjective search results, especially for non-experts in intellectual property analysis.
Innovation Solution
A method and device utilizing a generative AI model to design a metaframe structure, derive technology structures, generate search keywords, and perform content-based clustering to analyze and classify technology data, including trend analysis and discovery of promising candidate groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual processing of patent data is performed, then search results can be obtained, but time consumption and manpower requirements increase significantly
Solution Approach 1:
The patent replaces manual mechanical processing with an automated system comprising a generative AI model, clustering module, and analysis module. The generative AI model automatically generates technology structures and search keywords, the clustering module performs content-based clustering on documents, and the analysis module conducts trend analysis, eliminating the need for manual data processing while maintaining or improving accuracy.
Solution Approach 2:
The patent introduces an intermediary automated processing system between the input patent data and the final search results. This intermediary system includes multiple processing stages (generative AI model for structure generation, clustering module for document grouping, analysis module for trend identification) that systematically transform raw data into actionable insights, reducing both time consumption and human resource requirements.
2Productivity
If manual processing of patent data is performed, then search results can be obtained, but errors and subjective judgments increase
Solution Approach 1:
The patent replaces manual processing with an automated system that eliminates subjective judgment. The generative AI model consistently generates technology structures based on input data, the clustering module objectively groups documents using content-based algorithms, and the analysis module systematically identifies trends, ensuring high data consistency and eliminating human errors while maintaining high processing efficiency.
Solution Approach 2:
The patent implements a feedback mechanism where the system's output is continuously evaluated and refined. The generative AI model generates initial structures that are refined based on clustering results, and the analysis module produces trend insights that can be validated against the clustered data, creating a self-correcting system that improves reliability through iterative refinement.
3Adaptability or versatility
If vast amounts of patent data are accumulated, then technology coverage is improved, but processing complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the vast patent data into manageable clusters based on content similarity. The clustering module groups documents into thematic clusters, the analysis module identifies trends within each cluster, and the system generates structured outputs for each segment, making the processing of large datasets systematic and manageable while maintaining comprehensive technology coverage.
Solution Approach 2:
The patent creates a universal processing framework that handles diverse patent data through multiple functions. The generative AI model generates technology structures for any input data, the clustering module performs content-based grouping across different domains, and the analysis module conducts trend analysis universally applicable to various technology fields, enabling the system to manage complex data volumes through multi-functional processing.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
According to the present disclosure, a method for analyzing technology is provided including: an information collection step of designing a metaframe structure for keywords to be analyzed, deriving a technology structure based on the metaframe structure using a generative AI model, generating search keywords based on the derived technology structure, and searching and obtaining a plurality of documents based on the search keywords; and a technology classification step of refining the plurality of documents according to a similarity between the documents, performing preprocessing to utilize contents of the plurality of documents, and then performing detailed technology classification based on results obtained by performing content-based clustering, and a device for processing the method.