Agreement Analysis References for Searchable IP Conformance
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Solution Overview
Problem
Current systems lack a comprehensive, automated method for managing and analyzing intellectual property assets, particularly in associating and documenting relationships between various intellectual property documents, which complicates the analysis and utilization of these assets.
Innovation Solution
A system and method for automated or semi-manual processing of intellectual property analyses, including searching, editing, reporting, and viewing, that allows for the creation of claim charts and comparison charts, with features like automatic evaluation, population of claim language, and accommodation of non-standard formats, while enabling the assignment of context to analyses and relationships between intellectual property documents.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated analysis systems are implemented, then productivity and analysis speed improve, but the ability to document and manage relationships between intellectual property documents deteriorates
Solution Approach 1:
The system segments intellectual property analysis into multiple hierarchical levels: individual document analysis, relationship identification, and portfolio-level synthesis. This segmentation allows automated processing at each level while preserving relationship information through structured data models that capture associations between documents, claims, and prior art references.
Solution Approach 2:
The system introduces an intermediary relationship database that acts as a mediator between automated analysis processes and final output. This intermediary layer captures and stores relationships between intellectual property documents, claims, and prior art, ensuring that relationship information is preserved and can be retrieved for comprehensive analysis without slowing down the automated processing pipeline.
2Loss of information
If comprehensive relationship tracking is implemented, then information completeness improves, but system complexity increases
Solution Approach 1:
The system divides the complexity of relationship tracking into manageable segments organized by hierarchical levels (document-level, claim-level, portfolio-level) and relationship types (infringement, validity, dependency). This segmentation allows the system to handle comprehensive relationship tracking through modular components rather than a monolithic complex system.
Solution Approach 2:
The system changes the parameter of relationship representation from unstructured free text to structured data models with defined schemas. By parameterizing relationships with standardized attributes (relationship type, strength, direction, associated entities), the system achieves information completeness while reducing complexity through consistent data structures that are easier to process and query.
3Loss of information
If manual analysis methods are used, then relationship documentation capability is maintained, but productivity and efficiency deteriorate
Solution Approach 1:
The system implements self-service capabilities where the automated analysis process automatically identifies, extracts, and documents relationships between intellectual property documents without requiring manual intervention. The system serves itself by generating relationship annotations, creating structured data, and organizing information automatically, thereby maintaining relationship documentation capability while dramatically improving productivity.
Solution Approach 2:
The system replaces the mechanical manual process of relationship documentation with automated computational processes. Instead of manually reading, analyzing, and recording relationships, the system uses natural language processing, pattern recognition, and automated reasoning to identify and document relationships, substituting human mechanical effort with automated intelligent processing.
4Measurement precision
If discrete individual analyses are performed, then analysis precision is maintained, but time consumption and operational complexity increase
Solution Approach 1:
The system merges discrete individual analyses by identifying and consolidating common elements across multiple documents, such as shared prior art references, overlapping claim scopes, and common technical fields. By merging analyses at the relationship level while maintaining precision at the individual document level, the system reduces total analysis time without sacrificing the precision of individual assessments.
Solution Approach 2:
The system performs preliminary actions by pre-processing and indexing intellectual property documents to extract key features, claims, and references before actual analysis begins. This preliminary action creates a structured foundation that accelerates subsequent analyses, allowing the system to maintain precision while reducing time consumption through efficient reuse of pre-extracted information across multiple analyses.
Data Source
AI summary
A computer-enabled system, method, and medium provides intellectual property analyses, for example, patent claim charts, respective to the analyzed intellectual property and a target product or other intellectual property. Analyses are stored to enable searching/reporting across multiple analyses. Units of the analysis are associated with context, inherited, e.g., from the intellectual property document's assignment to a relative role within the organizational hierarchy; and associated with a context derived from the analysis itself. The analysis and respective documents and/or targets of the analysis can be searched/retrieved/analyzed from the hierarchical analysis, the context analysis, and/or the content of the analysis. Each analysis need not be stored as a separate document. The representation of the analysis may by static or dynamic. The target or annotations may be visually represented by an item such as a thumbnail or hyperlink, and the system associates the item with the appropriate application program.