Online Ad Interface With ML-Based Custom Content Editing

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Solution Overview

Problem

Small businesses and individuals face challenges in designing effective online advertisements due to limited budget, technical knowledge, and resources, making it difficult to efficiently create and analyze advertisement effectiveness.

Innovation Solution

A system and method utilizing a machine learning model to generate customized online advertisements based on user input and attributes extracted from user profiles, allowing for real-time generation and editing of visual and textual components.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If small businesses and individuals design advertisements manually with limited resources, then they maintain control over the design process, but the time consumption and cost increase significantly

Engineering Contradiction:
Improveadvertisement creation efficiencyVSAvoidtime for advertisement design and analysis
Core Design Contradiction:
ProductivityVSLoss of time

Solution Approach 1:

The system enables self-service by automatically generating advertisement content through machine learning models that analyze user profiles and create customized advertisements without requiring manual design input from users with limited resources

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The patent replaces the mechanical manual design process with an automated machine learning system that generates advertisement content, visual components, and performance analysis automatically, eliminating the need for manual advertisement creation and analysis tasks

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If manual advertisement design is used, then customization is possible, but the technical knowledge and expertise required create barriers for small businesses

Engineering Contradiction:
Improveadvertisement customization capabilityVSAvoidease of advertisement creation
Core Design Contradiction:
Adaptability or versatilityVSEase of operation

Solution Approach 1:

The system automatically extracts attributes from user profiles and generates customized advertisement content without requiring users to possess technical design knowledge or expertise, making the process accessible to small businesses and individuals

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The machine learning model dynamically adjusts advertisement parameters including visual components, text content, and design elements based on extracted user profile attributes, achieving customization automatically without manual intervention

Inventive Principle:
Principle #35Parameter changes

3Ease of manufacture

If traditional advertisement tools are used, then specific tasks like posting and data compilation are assisted, but the initial advertisement design remains a manual burden

Engineering Contradiction:
Improveease of advertisement posting and data compilationVSAvoidcomplexity of advertisement design process
Core Design Contradiction:
Ease of manufactureVSDevice complexity

Solution Approach 1:

The patent merges multiple previously separate tasks including advertisement design, content creation, visual component generation, and performance analysis into a single integrated machine learning system that handles the entire advertisement lifecycle automatically

Inventive Principle:
Principle #5Merging (Combining)

Solution Approach 2:

The machine learning system performs multiple functions including attribute extraction, content generation, visual component creation, and performance analysis within a single platform, eliminating the need for separate tools for each advertisement task

Inventive Principle:
Principle #6Universality (Multi-functionality)

Data Source

PatentEP4682807A1Interface for online content generation
Publication Date: 2026.01.21 META PLATFORMS INC
  • EP4682807A1 patent drawingFigure 1
  • EP4682807A1 patent drawingFigure 2
  • EP4682807A1 patent drawingFigure 3

AI summary

Systems and methods for generating advertisements via an online interface include extracting an attribute from a user profile in accordance with receiving user input at an interactive input form provided at a graphical user interface on a first computing device. The systems and methods also include generating, by a machine learning model, an advertisement that is customized based on the user input and the attribute. The advertisement includes an advertisement content component that includes at least one of a visual component or a text component. The systems and methods also include rendering, on the graphical user interface, an editable version of the advertisement. The advertisement content component is editable on the graphical user interface.