Contract Data Tree Generation for Legal Research Efficiency
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Solution Overview
Problem
Current data management systems face challenges in efficiently processing and analyzing large volumes of contract data due to complex tree relationships between contracts, leading to time-consuming legal research and difficulties in determining the exact location of specific contract data.
Innovation Solution
A contract data management module that automatically generates a data tree structure using processors and memories, storing contract metadata with relationship information, and utilizing a search engine to create linkages between data points, generating an API and visual representation of inter-dependencies between contracts, facilitating tree-based searches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If contracts are stored in a database tracking only immediate parent relationships, then data storage is simple, but legal research requires reading dozens to hundreds of agreements to identify scope of work
Solution Approach 1:
The patent segments the contract data structure into hierarchical levels (master agreements, amendments, schedules, exhibits) and creates a visual tree structure that breaks down the complex relationships into manageable segments. This allows researchers to navigate specific portions of the contract hierarchy without reading entire documents, resolving the contradiction between simple storage and efficient research.
Solution Approach 2:
The patent introduces an intermediary visual interface layer between the database and the researcher. This intermediary automatically generates and displays the complete contract tree structure, showing all parent-child relationships across multiple levels. Researchers can visually trace relationships and identify scope of work without manually reading dozens of agreements, thus reducing research time while maintaining simple database storage.
2Reliability
If the contract data structure includes multiple parent relationships and hierarchical levels, then comprehensive contract relationships are captured, but determining the exact location of specific contract data becomes confusing
Solution Approach 1:
The patent implements a nested visual tree structure where contracts are organized in hierarchical levels (master agreements containing amendments, schedules, and exhibits). Each level is visually nested within its parent, creating a clear nested doll-like structure. This maintains accurate multi-parent relationships while providing visual cues that make locating specific contract data straightforward, resolving the contradiction between relationship accuracy and ease of operation.
Solution Approach 2:
The patent adds a visual dimension to the contract data structure by displaying relationships in a tree diagram format rather than traditional tabular database views. This dimensional transformation allows users to perceive hierarchical relationships and exact data locations spatially, making it easier to navigate complex multi-parent relationships while maintaining complete relationship accuracy.
3Manufacturing precision
If manual analysis of contract relationships is performed, then data quality can be managed, but processing speed decreases significantly as data volume increases
Solution Approach 1:
The patent implements automated self-service functionality where the system automatically generates the complete contract tree structure from database entries, automatically identifies parent-child relationships across multiple levels, and automatically displays the hierarchical structure. This eliminates the need for manual analysis while maintaining data quality, thereby resolving the contradiction between quality management and processing speed.
Solution Approach 2:
The patent performs preliminary automated processing of contract relationships when data is entered or updated in the database. The system pre-generates and stores the complete tree structure and relationship information, so that when researchers need to analyze contracts, the work is already done. This preliminary action maintains data quality while enabling rapid retrieval and analysis, resolving the speed-quality contradiction.
Data Source
AI summary
A system and method for automatic generation of a data tree structure are disclosed. A database stores contract metadata associated with a plurality of contracts. The metadata includes relationship information data regarding parentage and/or child relationship between a particular contract and other contracts among the plurality of contracts. A processor operatively connects to the database via a communication network and accesses the database via the communication network to retrieve the contract metadata including the relationship information data. The processor also implements a search engine; stores the retrieved contract metadata including the relationship information data onto the search engine for creating a linkage between data points; and automatically generates, based on the created linkage between the data points, both an application programming interface (API) and a data tree structure that displays inter-dependency between two or more sets of contracts among the plurality of contracts.