Public Display Ad Generation From Filtered User Comments
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Solution Overview
Problem
Existing advertisement methods in public places lack personalization and effectiveness in engaging users, failing to leverage user input for tailored and engaging advertisements.
Innovation Solution
A system and method utilizing a server and public display device to collect user input through a website, filter and process it using neural networks to generate personalized advertisements based on user feedback, and display them on public display devices.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If traditional advertisement methods are used in public places, then advertisements can be displayed to the public, but the advertisements lack personalization and user engagement
Solution Approach 1:
The system collects user feedback through text comments submitted via a website, processes this feedback through neural network models to generate personalized advertisements, and displays them on public screens. This creates a closed-loop feedback system where user input directly influences advertisement content, enabling personalization while maintaining ease of operation through automated processing.
Solution Approach 2:
The generative neural network model automatically generates personalized advertisement content from user comments without requiring manual intervention. The system self-services by taking raw user feedback and transforming it into tailored advertisements, reducing operational complexity while enhancing personalization capabilities.
2Adaptability or versatility
If user input is collected and processed to create personalized advertisements, then advertisement relevance to users increases, but system complexity increases
Solution Approach 1:
The server acts as an intermediary between users and the public display system. It collects user comments, processes them through filtering and generative neural network models, and generates personalized advertisements. This intermediary layer manages the complexity of processing user input while presenting a simple interface to both users and the display system.
Solution Approach 2:
The patent replaces manual advertisement creation and curation with automated neural network models. The generative model automatically transforms user comments into personalized advertisement content, eliminating the need for manual content creation and reducing system operational complexity despite the sophisticated processing involved.
3Productivity
If manual advertisement creation is used, then system simplicity is maintained, but advertisement effectiveness and user engagement decrease
Solution Approach 1:
The system changes the parameters of advertisement creation from static, pre-defined content to dynamic, user-generated content. By transforming user comments into personalized advertisements through neural network processing, the system achieves higher effectiveness and engagement while managing processing complexity through automated workflows.
Data Source
AI summary
A method for creating an advertisement based on user input includes displaying, by a public display device, a link for inputting user-input text comments about a predetermined merchandise; in response to receipt of a user-input text comment, performing, by a server, a filtering operation so as to obtain a filtered input string; feeding the filtered input string into a generative neural network model, so as to obtain an advertising text file; generating a user-related advertisement for the predetermined merchandise based on at least the advertising text file, and transmitting the user-related advertisement to the public display device for displaying.