Generative AI Patent Claim Mapping for Portfolio Scope Analysis
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Solution Overview
Problem
Existing patent management systems struggle to efficiently determine the scope and relevance of patent claims, leading to inefficiencies in managing large portfolios and impeding timely decision-making.
Innovation Solution
A generative artificial intelligence (AI) tool is employed to analyze patent claim texts, identify common concepts, and generate an interactive matrix and graphic user interface for visualizing the relationship between these concepts and claims, facilitating efficient portfolio management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional patent management systems are used to analyze patent claims, then the analysis process becomes manual and time-consuming, but the system lacks the capability to efficiently determine scope and relevance of claims
Solution Approach 1:
The patent replaces manual mechanical analysis of patent claims with an automated AI-based system that uses natural language processing and machine learning algorithms to extract, compare, and analyze claim elements, thereby eliminating the need for time-consuming manual review while maintaining or improving analysis quality
Solution Approach 2:
The patent introduces an intermediary AI processing layer between the raw patent claims and the final analysis results. This intermediary system automatically parses claims, identifies key elements, compares them across multiple patents, and generates structured outputs, serving as a mediator that bridges the gap between unstructured claim text and actionable insights
2Loss of time
If manual methods are used to determine patent claim scope, then the process is simple in terms of system complexity, but it impedes timely decision-making in large patent portfolios
Solution Approach 1:
The patent segments the complex task of patent claim analysis into distinct modular components: claim parsing, element extraction, similarity comparison, scope determination, and result visualization. Each module handles a specific aspect of the analysis, making the overall complex system manageable, maintainable, and scalable while enabling rapid processing of large patent portfolios
3Productivity
If comprehensive analysis of all patent claims is performed manually, then accuracy can be maintained, but the process becomes inefficient for large portfolios
Solution Approach 1:
The patent incorporates feedback mechanisms where the AI system's initial analysis results are validated against established patent criteria and legal standards, with iterative refinement processes that adjust the analysis based on identified patterns and exceptions, thereby maintaining high accuracy while processing large volumes of claims efficiently
Data Source
AI summary
A method may include receiving a plurality of claim texts corresponding to a plurality of claims originating from a patent document; identifying, using a generative artificial intelligence tool (generative AI tool), a common concept shared between a set of claim texts of the plurality of claim texts; presenting the common concept in a tabular form including a first column listing the common concept and additional columns corresponding to respective claim texts of the pluralities of claim texts indicating a presence or absence of the common concept; verifying, using a non-generative AI algorithm that the common concept has corresponding representations within the set of claim texts; and in response to the verifying, generating an interactive matrix, wherein the interactive matrix visually represents a relationship between the common concept and the set of claim texts.