18477772. SYSTEMS AND METHODS FOR FEEDBACK-GUIDED CONTENT GENERATION simplified abstract (ADOBE INC.)

SYSTEMS AND METHODS FOR FEEDBACK-GUIDED CONTENT GENERATION

Organization Name

ADOBE INC.

Inventor(s)

Rebecca Dorothy West of Auburn CA (US)

Lauren Dest of Austin TX (US)

Mihir Naware of Redwood City CA (US)

Elliot Axel Patrick Puzenat of Le Plessis Robinson (FR)

Stephen Becigneul of Levallois-Perret (FR)

Alexis Tessier of Eckwersheim, Bas-Rhin (FR)

Roger K. Brooks of Palo Alto CA (US)

Suman Basetty of Fremont CA (US)

Kimberly K. Lenox of Orinda CA (US)

Anil Kamath of Los Altos Hills CA (US)

SYSTEMS AND METHODS FOR FEEDBACK-GUIDED CONTENT GENERATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 18477772 titled 'SYSTEMS AND METHODS FOR FEEDBACK-GUIDED CONTENT GENERATION

Simplified Explanation: The patent application describes a method for content generation using a user experience platform and machine learning model to modify content distribution campaigns based on feedback.

Key Features and Innovation:

• Identification of content distribution campaigns by a user experience platform.
• Obtaining feedback for the campaigns.
• Generating modified content using a machine learning model.

Potential Applications: This technology can be applied in digital marketing, advertising, and content creation industries to optimize content distribution strategies.

Problems Solved: This technology addresses the need for personalized and data-driven content generation to improve campaign performance and user engagement.

Benefits:

• Enhanced targeting and customization of content.
• Improved campaign effectiveness and ROI.
• Streamlined content creation processes.

Commercial Applications: Optimizing digital marketing campaigns, improving advertising strategies, and enhancing user experience on various platforms.

Prior Art: Readers can explore prior art related to content generation, user experience platforms, and machine learning models in the fields of digital marketing and advertising.

Frequently Updated Research: Stay updated on advancements in machine learning algorithms, user experience design, and content optimization techniques relevant to this technology.

Questions about Content Generation Technology: 1. How does machine learning contribute to the modification of content distribution campaigns? 2. What are the key advantages of using a user experience platform in content generation and distribution?

Original Abstract Submitted

A method, non-transitory computer readable medium, apparatus, and system for content generation are described. An embodiment of the present disclosure includes identifying, by a user experience platform, a content distribution campaign. The user experience platform obtains feedback for the content distribution campaign. Embodiments of the present disclosure further include generating content for a modified content distribution campaign based on the feedback using a machine learning model.