Interactive Patent Data Visualization via Co-occurrence Network Graphs
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Solution Overview
Problem
Current Patent database display formats, such as pie charts and technological clustering, are limited in extracting information due to opacity in data processing and subjectivity in interpretation, making it difficult to identify niche applications and technological connections.
Innovation Solution
A method for interactive exploration of Patent data using co-occurrence analysis and graphical representation, where users can interrogate databases, process bibliographical data, and display results in interactive network graphs to visualize technological category co-occurrences, allowing for adjustable parameters and filtering.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pie charts or technological clustering are used to display patent data, then visual representation is provided, but information extraction capability is limited and interpretation becomes subjective
Solution Approach 1:
The patent replaces traditional visual display methods (pie charts, clustering algorithms) with a network graph based on co-occurrence analysis. This substitution transforms the mechanical visualization process into a data-driven network representation where nodes represent patent documents and edges represent co-occurrence relationships, enabling more accurate information extraction while maintaining visual intuitiveness
Solution Approach 2:
The patent changes the fundamental parameter for visualization from spatial positioning (clustering) or proportional area (pie charts) to co-occurrence frequency. By using co-occurrence analysis to determine connection strengths between patent documents, the system provides objective, quantifiable relationships that improve information extraction while reducing subjective interpretation
2Ease of operation
If clustering algorithms are used for technological segmentation, then visual organization is achieved, but the segmentation process becomes opaque and difficult to interpret
Solution Approach 1:
The patent substitutes opaque clustering algorithms with transparent co-occurrence analysis. Instead of using black-box segmentation that requires complex mathematical operations to interpret, the system directly counts and displays co-occurrence frequencies between patent documents, making the segmentation process transparent and easily interpretable while maintaining visual organization through network graphs
3Ease of operation
If traditional display formats are used, then simple visualization is provided, but identification of niche applications and technological connections is difficult
Solution Approach 1:
The patent adds a new dimension to patent visualization by incorporating co-occurrence frequency as a quantitative metric. Instead of relying solely on spatial positioning or proportional area, the system uses network edge weights to represent the strength of technological connections, enabling identification of niche applications through rare but significant co-occurrence patterns while maintaining visual simplicity through graph representation
Data Source
AI summary
A method is provided of communication between a user and a database of Patents and also of the display and the interactive exploration of data on information of interest relating to Patents/Patent applications. The method comprises:the generation, by means of an access interface, of a request allowing the database to be interrogated based on at least one selection criterion entered into the access interface;the interrogation of the database by means of the request and the loading of bibliographical data for the Patents/Patent applications found, the downloaded bibliographical data comprising data on the technological category;the processing of the bibliographical data, the processing comprising an analysis of co-occurrences comprising the determination of a number of co-occurrences of data on the technological category for all of the Patents/Patent applications found;the displaying, in interactive graphical and/or textual form, of a result and/or of an interpretation of the analysis of co-occurrences.