User-Input Ad Generation for Personalized Public Displays
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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 that utilizes user input through a filtering and generative neural network model to create personalized advertisements, incorporating user comments, sentiments, and relevance analysis to generate user-related advertisements for public display.
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 and stores user feedback, comments, and preference data in advance through various input channels (social media, surveys, website interactions). This preliminary data collection enables the advertisement generation system to access pre-processed user insights when creating personalized advertisements, eliminating the need for real-time data gathering and allowing faster personalized ad generation.
Solution Approach 2:
The patent introduces an artificial intelligence system as an intermediary between user feedback and advertisement creation. This AI intermediary processes user inputs, extracts relevant insights, and translates them into personalized advertisement content. The AI acts as a mediator that bridges the gap between raw user data and tailored advertisements, enabling personalization without requiring direct real-time user interaction during ad creation.
2Adaptability or versatility
If personalized advertisements are created using user input, then user engagement and relevance increase, but system complexity increases
Solution Approach 1:
The patent divides the advertisement creation system into distinct functional modules: a data collection module that gathers user feedback, a processing module that analyzes the feedback using AI, a generation module that creates personalized advertisements, and a display module that presents the ads. This segmentation allows each component to be optimized independently and simplifies the overall system architecture by distributing complexity across specialized subsystems rather than requiring a monolithic complex system.
Solution Approach 2:
The system employs artificial intelligence that operates autonomously to analyze user feedback and generate personalized advertisements without requiring manual intervention. The AI self-service capability automatically processes incoming user data, extracts relevant patterns, and produces tailored ad content, reducing the need for human operators and simplifying system management despite the sophisticated personalization capabilities.
3Measurement precision
If user feedback is collected and processed in real-time, then advertisement relevance improves, but processing time and computational resources increase
Solution Approach 1:
The system performs preliminary processing of user feedback by pre-categorizing, filtering, and structuring data as it is collected. User inputs are organized into meaningful patterns and insights before the advertisement generation process begins. This advance preparation reduces the computational burden during actual ad creation, enabling fast generation of relevant personalized advertisements without requiring intensive real-time processing.
Data Source
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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.