Automated Report Generation System Using Machine Learning

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Solution Overview

Problem

The creation of professional reports is time-consuming and often results in uneven quality due to the need for domain knowledge and writing skills, with conventional report generation processes limited to simple data-based reporting.

Innovation Solution

A system utilizing machine learning and libraries (personal, organization, and industry) for dynamically generating reports, featuring content tagging, sentiment prediction, and customizable templates to enhance report quality and efficiency.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If conventional manual report creation methods are used, then report quality can be maintained through domain knowledge and writing skills, but the time required to create reports is very long

Engineering Contradiction:

Improvereport qualityVSAvoidtime required to create reports

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The patent replaces the manual mechanical process of report creation with an automated system that uses machine learning models, natural language processing, and data processing algorithms to generate reports automatically, thereby reducing time while maintaining quality through systematic content generation

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables reports to generate themselves automatically by pulling data from multiple sources, applying templates, and assembling content without requiring manual writing or domain expertise from users, allowing the system to serve itself in the report creation process

Inventive Principle:

Principle #25Self-service

2Loss of time

If efforts are made to lower the length of time needed to create reports, then time efficiency is improved, but report quality becomes uneven and inferior

Engineering Contradiction:

Improvetime required to create reportsVSAvoidreport quality

Core Design Contradiction:

Loss of timeVSManufacturing precision

Solution Approach 1:

By replacing manual report creation with an automated system that uses machine learning models and structured templates, the system achieves both speed and consistency, eliminating the trade-off between time efficiency and quality uniformity that plagues manual processes

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system changes the parameters of report generation by using configurable templates, data sources, and machine learning models that can be adjusted to maintain quality standards while automating the process, allowing quality to be controlled through system parameters rather than manual skill

Inventive Principle:

Principle #35Parameter changes

3Productivity

If simple data-based reporting processes are used, then report generation is quick and straightforward, but the ability to create professional reports with domain knowledge is limited

Engineering Contradiction:

Improvereport generation speedVSAvoidcapability to create professional reports

Core Design Contradiction:

ProductivityVSAdaptability or versatility

Solution Approach 1:

The system achieves multi-functionality by combining data retrieval, analysis, template application, and professional content generation in a single platform that can handle both simple data reporting and complex professional report creation with domain-specific knowledge

Inventive Principle:

Principle #6Universality (Multi-functionality)

Solution Approach 2:

The system replaces simple data reporting with an intelligent automated system that uses machine learning and natural language processing to generate professional-grade reports, thereby enhancing the capability beyond basic data presentation while maintaining automation benefits

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Data Source

PatentUS11461534B2System for dynamically generating content for professional reports based on continuously updated historical data

Publication Date: 2022.10.04 TECH FOOTING LLC

AI summary

A system and method of generating a professional report. The method includes selecting a report subject matter, tagging the report subject matter, providing report suggestions based on the report subject matter and a scoring subprocess, and selecting library content. The method then includes creating a draft report using the selected library content, editing the draft report, submitting the draft report for review, and providing a finalized report.