IP Landscaping Platform Clustering and Scoring
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Solution Overview
Problem
Analyzing and identifying similar intellectual-property portfolios, especially for entities with large portfolios, is challenging due to the complexity of managing and visualizing large datasets of patents and patent applications.
Innovation Solution
An intellectual-property landscaping platform that uses a landscaping component, scoring component, and data store to seed user-driven searches, cluster IP assets by technical fields, and generate spatial representations, allowing for the identification of similar entities and visualizing IP asset landscapes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional methods are used to analyze large intellectual-property portfolios, then comprehensive analysis coverage is achieved, but the complexity of managing and visualizing the data becomes unmanageable
Solution Approach 1:
The patent segments large IP portfolios into smaller, manageable clusters based on technical fields, legal status, and other characteristics. This allows the system to handle comprehensive IP portfolios while maintaining manageable complexity through organized groupings and hierarchical structures.
Solution Approach 2:
The patent introduces an intermediary processing layer that automatically analyzes, categorizes, and structures IP portfolio data before presentation. This intermediary system manages the complexity by transforming raw data into organized, visualizable formats without requiring direct manual management of the entire portfolio.
2Measurement precision
If detailed analysis of large IP portfolios is performed, then identification accuracy of similar entities improves, but the time and computational resources required increase significantly
Solution Approach 1:
The patent performs preliminary actions by pre-processing and pre-categorizing IP portfolio data into structured clusters before similarity analysis. This preliminary organization enables faster and more accurate identification of similar entities by reducing the search space and establishing meaningful groupings in advance.
Solution Approach 2:
The patent replaces manual or simple mechanical analysis methods with automated computational systems that use algorithms to analyze IP portfolios, calculate similarity metrics, and generate visualizations. This substitution enables detailed analysis of large portfolios within reasonable timeframes through efficient computer-based processing.
3Loss of information
If comprehensive IP portfolio data is collected and stored, then analysis completeness is improved, but the difficulty of visualizing and interpreting the data increases
Solution Approach 1:
The patent transforms complex multi-dimensional IP portfolio data into visual representations that add spatial and graphical dimensions. By converting tabular or textual data into visual clusters, networks, and maps, the system enables effective visualization and interpretation of comprehensive IP portfolio information while maintaining analysis completeness.
Data Source
AI summary
Systems and methods for generation and use of intellectual-property (IP) landscaping platform architectures are disclosed. A landscaping component may be utilized to produce refined clusters of IP assets using user seeded searches in varying areas of interest, such as, for example, target technical fields, targeted publications, targeted products, and/or competitor entity portfolios. The landscaping component may be further utilized to produce an interactive graphical element including a spatial representation of the clusters of IP assets. The interactive graphical element may include various functionalities and/or information associated with the clusters of IP assets. A scoring component may be utilized to determine i) an overall coverage and/or identify gaps in coverage; ii) a potential market opportunity; and iii) a potential exposure associated with the IP assets included in the targeted technical fields, subject matters, and/or competitor entities portfolios.