Automated Report Generation via Extracted Mathematical Relationships

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Solution Overview

Problem

Existing methods face difficulties in replicating spreadsheet report formats with new data sets when mathematical relationships are not directly portable, especially with large volumes of data, requiring regeneration of entire spreadsheets.

Innovation Solution

A method is developed to determine mathematical relationships between raw and derived data, generating executable code to produce reports from new data sets, optimizing operations and using Java-based implementations for efficient report generation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If the entire spreadsheet is regenerated when mathematical relationships are not directly portable, then the report format can be replicated for new data sets, but the processing time and computational resources increase significantly

Engineering Contradiction:

Improvereport format replicationVSAvoidspreadsheet regeneration time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The patent extracts mathematical relationships from the original spreadsheet report into a separate, portable format. This allows the structural logic and formulas to be separated from the raw data, enabling reuse of the report format with new data sets without regenerating the entire spreadsheet from scratch.

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The patent performs preliminary analysis to identify and extract mathematical relationships before the actual report generation. By pre-processing the original report to capture its structural logic, the system prepares reusable components that can be quickly applied to new data sets, avoiding time-consuming regeneration processes.

Inventive Principle:

Principle #10Preliminary action

2Productivity

If mathematical relationships are extracted and stored separately, then report generation becomes faster and more efficient, but the system complexity increases

Engineering Contradiction:

Improvereport generation speedVSAvoidsystem architecture

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent creates a simplified copy of the mathematical relationships from the original spreadsheet. Instead of copying the entire complex spreadsheet structure, only the essential formulas and logical relationships are extracted and stored in a lightweight, portable format that can be easily reused.

Inventive Principle:

Principle #26Copying

Solution Approach 2:

The patent segments the spreadsheet report into distinct components: raw data, mathematical relationships, and output format. This segmentation allows each component to be independently processed and reused, improving efficiency without requiring complex integration of entire spreadsheet structures.

Inventive Principle:

Principle #1Segmentation

3Adaptability or versatility

If the spreadsheet structure is made highly portable and reusable, then adaptability to new data sets improves, but the ability to handle complex mathematical relationships may be compromised

Engineering Contradiction:

Improvedata set compatibilityVSAvoidmathematical relationship accuracy

Core Design Contradiction:

Adaptability or versatilityVSManufacturing precision

Solution Approach 1:

The patent changes the parameter representation of mathematical relationships from proprietary spreadsheet-specific formats to standardized, language-agnostic expressions. This allows complex mathematical relationships to be preserved accurately while enabling portability across different data sets and systems.

Inventive Principle:

Principle #35Parameter changes

Data Source

PatentUS10872129B2Methods for providing automated scalable strategic modelling and devices thereof

Publication Date: 2020.12.22 JPMORGAN CHASE BANK NA

AI summary

Various methods, apparatuses, and media for producing a report are provided. A first input that includes raw data and derived data is received, and mathematical relationships between the derived data and the raw data are determined. The mathematical relationships are used for generating executable code, which is then applied to newly inputted raw data to produce the report.