Big data-driven intellectual property value dynamic evaluation and transaction matching system
By leveraging big data-driven multi-source data collection and intelligent analysis, combined with dynamic modeling and intelligent matching algorithms, the subjectivity and lag issues of traditional intellectual property valuation have been resolved. This enables real-time valuation of intellectual property value and efficient transaction matching, thereby improving market liquidity and resource allocation efficiency.
CN121660181APending Publication Date: 2026-03-13SUZHOU SHANZHANGLI INTELLIGENT TECH CO LTD
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Patent Information
- Application Number
- CN202511870419.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-12
- Publication Date
- 2026-03-13
AI Technical Summary
Technical Problem
Traditional intellectual property valuation methods rely on expert experience and static data, which are highly subjective, outdated, and difficult to quantify, resulting in insufficient market liquidity and low transaction matching efficiency.
Method used
It employs big data-driven multi-source data acquisition and intelligent analysis technologies, combined with dynamic modeling, to achieve real-time and objective assessment of intellectual property value, and facilitates transaction matching through intelligent matching algorithms.
Benefits of technology
It enables real-time dynamic assessment of intellectual property value and efficient transaction matching, thereby improving market liquidity and resource allocation efficiency.
✦ Generated by Eureka AI based on patent content.
Abstract
The invention discloses a big data-driven intellectual property value dynamic evaluation and transaction matchmaking system, and relates to the fields of big data analysis, artificial intelligence, financial science and technology and intellectual property management. Aiming at the problems of high subjectivity, update lag, low transaction matching efficiency and the like of traditional intellectual property evaluation, the system integrates multi-source heterogeneous data acquisition and fusion functions, a dynamic value evaluation model is constructed based on an AI technology, and real-time value quantification is realized by integrating multi-dimensional factors; supply and demand parties are accurately matched through an intelligent matching algorithm, risk early warning, a credit evaluation mechanism and an automatic transaction management process are matched, and visual decision support is provided. Experiments show that the correlation between the system evaluation result and the market trading price is improved by more than 20%, the matching success rate is more than 70%, the period is shortened by 40%, and the risk early warning accuracy is significantly superior to that of a traditional method. The system can be widely applied to the fields of intellectual property operation, investment and financing, scientific and technological achievement transformation and the like, evaluation objectivity and transaction efficiency are effectively improved, and market resource allocation is optimized.
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