Computerized Patent Portfolio Analysis Method
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Solution Overview
Problem
Current methods for analyzing patent portfolios are inefficient in identifying non-obvious relationships between patents, especially in large datasets, leading to information overload and difficulties in strategic decision-making, such as licensing, acquisition, and innovation, due to limitations in prior art search tools and methods.
Innovation Solution
A computerized method for analyzing patent relationships using a database to determine nexus points between patents, including technological, historical, and chronological connections, allowing for efficient visualization and identification of relevant relationships within and between patent portfolios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional prior art search tools and methods are used to analyze patent portfolios, then basic patent information can be retrieved, but non-obvious relationships between patents cannot be identified efficiently
Solution Approach 1:
The patent portfolio analysis is segmented into multiple dimensions including technological relationships, citation relationships, chronological relationships, and ownership relationships. Each dimension is analyzed separately through dedicated search queries, allowing comprehensive relationship identification without overwhelming complexity
Solution Approach 2:
A computerized search system acts as an intermediary between the user and the patent database, automatically executing complex multi-criteria searches across multiple patent portfolios. The system retrieves and processes relationship data without requiring manual analysis, thereby identifying non-obvious relationships efficiently
2Quantity of substance
If large patent portfolios are analyzed using conventional methods, then complete patent data can be accessed, but information overload occurs making strategic decision-making difficult
Solution Approach 1:
The system extracts specific relationship information from large patent portfolios by executing targeted search queries for different relationship types. Rather than presenting all patent data, it extracts only the relevant relationship patterns that provide strategic insights for licensing, acquisition, and innovation decisions
Solution Approach 2:
The analysis transitions from traditional single-dimension patent searching to multi-dimensional relationship analysis. The system evaluates patents across technological, citation, chronological, and ownership dimensions simultaneously, transforming raw patent data into multi-faceted relationship insights that prevent information overload
3Measurement precision
If manual analysis methods are used to identify patent relationships, then detailed examination is possible, but the process becomes time-consuming and inefficient
Solution Approach 1:
Manual mechanical analysis of patent relationships is replaced with automated computerized search systems. The system executes complex queries across multiple patent portfolios, automatically retrieving and analyzing technological, citation, chronological, and ownership relationships without human intervention, thereby maintaining analysis depth while dramatically reducing time consumption
Data Source
AI summary
The method of the present invention provides a labor and time saving ability to determine interrelationships within patents determined by searching, via a computer system, through patent fields to see if one or more particular pieces of alphanumeric data are common to any of the patents in the database in which the field indicia are located. Such commonality is searchable in backward or forward direction, or both, from, for example, one patent of particular interest. The method allows for presentation of families of interrelated patents within minutes rather than hours, weeks or longer by utilizing computer based technology. Further, the methodology allows for determinations of interrelationships within desired degrees of separation by manipulation of the indicative data to be searched.