Database Output Value Determination for Automated Deadline Calculation
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Solution Overview
Problem
Law firms face challenges in accurately and efficiently calculating deadlines due to the reliance on manual and error-prone methods, which can lead to serious consequences such as reinstatement cases and liability claims.
Innovation Solution
A computer-implemented method using machine learning models to automate the determination of numerical and text logic-related base values from text and image files, followed by calculation reference values, to provide accurate output values for data processing, including automated document creation and reminders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual methods are used to calculate deadlines, then lawyers can review and verify calculations, but the process is time-consuming and error-prone
Solution Approach 1:
The patent replaces manual mechanical calculation methods with an automated computer-implemented system that uses machine learning models to extract base values from documents, determine calculation reference values, and compute output values (deadlines) automatically, eliminating manual intervention while maintaining accuracy
Solution Approach 2:
The system enables self-service by automatically processing documents and calculating deadlines without requiring lawyer intervention for the calculation itself, while still allowing lawyers to review and verify results when needed, thus freeing them from time-consuming manual calculations
2Productivity
If automated machine learning models are used to determine output values, then calculation speed and consistency improve, but system complexity increases
Solution Approach 1:
The patent segments the complex processing task into distinct modular steps: extracting base values from documents, determining calculation reference values using machine learning models, and computing output values. This modular architecture manages complexity by making each component independent and well-defined
Solution Approach 2:
The system introduces intermediary components (machine learning models trained on legal documents) that act as mediators between raw document data and final deadline calculations, simplifying the overall process by handling the complexity of interpretation and calculation automatically
3Measurement precision
If multiple machine learning models are used to determine reference values, then calculation accuracy improves, but processing time increases
Solution Approach 1:
The patent applies preliminary action by pre-training machine learning models on extensive legal document datasets before deployment. This pre-processing ensures that when the models are used for actual deadline calculations, they can quickly and accurately determine reference values without requiring extensive processing time during production use
Data Source
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AI summary
A computer-implemented method for determining at least one output value for data processing in a database, comprising the steps of: - determining (S1) at least one numeric and/or text logic-related base value from a text and/or image file; - determining (S2) a computational reference and/or a text logic reference based on the base value and/or the text and/or image file by at least one machine learning model; - determining (S3) the at least one output value by the at least one machine learning model based on the base value and/or the computational reference and/or the text logic reference; and - providing (S4) the at least one output value for data processing in the database.