Computer Architecture for Automated Patent Portfolio Quantification
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Solution Overview
Problem
The conventional patent process is inefficient and ineffective in managing, protecting, and valuing technological innovations across multiple scientific fields, leading to imbalanced and poorly protected patent portfolios, resulting in wasted resources and missed opportunities.
Innovation Solution
An improved computer system utilizing machine learning and artificial intelligence to quantify technologies into market-tech units (MTUs), calculate generational and phase development data, assess innovation levels, and determine optimal patent protection strategies, ensuring a balanced and high-quality patent portfolio.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional patent process is used to manage and protect technological innovations, then patent protection is provided, but the process is inefficient and ineffective leading to imbalanced and poorly protected patent portfolios
Solution Approach 1:
The system enables self-service through automated patent analysis and strategy generation. The computer system automatically quantifies technologies into market-tech units, calculates generational and phase development data, assesses innovation levels, and determines optimal patent protection strategies without requiring manual intervention, thereby improving both efficiency and protection quality
Solution Approach 2:
The patent process replaces manual mechanical operations with automated computer-based systems. Machine learning algorithms and artificial intelligence models substitute for human analysts in quantifying technologies, calculating development data, and determining patent strategies, leading to more consistent and efficient patent portfolio management
2Loss of energy
If conventional patent process is used, then patent applications are filed, but resources are wasted and opportunities are missed due to inefficiency
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring patent portfolio balance and quality. The computer system analyzes patent data, compares it against target portfolios, and provides feedback to adjust patent strategies in real-time, ensuring resources are allocated efficiently and opportunities are captured before they are lost
Solution Approach 2:
The system performs preliminary actions by pre-quantifying technologies into market-tech units and pre-calculating generational and phase development data before patent filing decisions are made. This advance preparation enables more informed and efficient patent strategy formulation, reducing resource waste in later stages
Data Source
AI summary
A computer includes an improved architecture of a computing entity (CE) processing core section, a technology level (TL) co-processor section, a system database section, and a memory section, which stores a CE operating system and a TL operating system. The database section stores TL data operands regarding quantified technologies and the memory section further stores TL system applications, and TL user applications. The CE processing core section executes the TL operating system and the CE operating system. The TL co-processor section executes TL system application(s), in accordance with control of the TL operating system and the CE operating system, to produce TL data operands regarding quantified technologies from a large number of MSBTP documents. The TL co-processor section executes TL user application(s), in accordance with control of the TL operating system and the CE operating system, to produce a digital representation of a characteristic of the quantified technology for display.