Technology Transfer Data Processing with Bidirectional Value Evaluation
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Solution Overview
Problem
Current technology transfer methods lack a practical and effective data mining tool for optimizing the transfer and transformation of scientific and technological achievements, failing to provide comprehensive information interaction capabilities that meet the requirements of technology transfer offices.
Innovation Solution
A general information interaction method for technology transfer offices, involving data processing instructions, feature extraction, and processing tasks using patent network models, which includes patent information analysis, trend analysis, citation analysis, regional analysis, litigation risk analysis, intellectual property value evaluation, and bidirectional value evaluation to facilitate effective interaction and decision-making.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional technology transfer methods are used, then the process can be completed with basic operations, but the efficiency and effectiveness of technology transfer are insufficient due to lack of specialized data mining tools
Solution Approach 1:
The patent segments the technology transfer process into multiple specialized modules including patent information analysis, trend analysis, citation analysis, regional analysis, litigation risk analysis, intellectual property value evaluation, and bidirectional value evaluation. Each module handles specific aspects of data processing independently, improving overall transfer efficiency without overwhelming system complexity through modular design.
Solution Approach 2:
The patent creates a multi-functional information interaction system that performs diverse functions (data collection, analysis, evaluation, risk assessment) within a unified platform. This universal system handles various types of technology transfer tasks simultaneously, improving productivity while maintaining manageable complexity through integrated architecture.
2Measurement precision
If comprehensive data analysis is performed to improve decision-making, then the accuracy of technology transfer decisions is improved, but the time and computational resources required increase
Solution Approach 1:
The patent performs preliminary data collection, cleaning, and organization before actual analysis. Patent information, trend data, citation data, and other relevant data are pre-processed and stored in structured formats, enabling faster and more accurate decision-making without excessive processing time during the actual evaluation phase.
Solution Approach 2:
The patent replaces manual data analysis with automated computational systems including machine learning models for value evaluation, algorithms for trend prediction, and automated risk assessment tools. This substitution significantly improves decision accuracy while reducing the time and human resources required for comprehensive analysis.
Data Source
AI summary
A method for data processing and interactive information exchange with feature data extraction and bidirectional value evaluation for technology transfer is provided. During the process, a data processing instruction is formed after receiving a user operation instruction, and the corresponding data is obtained in accordance with the data processing instruction. Then, the corresponding data is processed to obtain specified data with feature data extraction; and the corresponding task for the specified data is being run to obtain a corresponding processing result, including a bidirectional value evaluation between the user and the processing result. A computer is also provided for use in connection with the method, where patent information is collected from the patent literature and subjected to processing, sorting, and analysis.