Dynamic Advertisement Text Generation System
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Solution Overview
Problem
Traditional methods of generating text for advertisements are inflexible and costly, especially in the context of web-based advertising, where static text fails to maximize the utility and potential value of advertisements due to the rapid growth of the Internet and the need for customization to target different audiences and promotions.
Innovation Solution
A system and method for dynamically generating text associated with advertisements using a core message and attributes of the advertiser and user, where customization is determined based on user and advertiser attributes, and natural language models are used to create modified text if customization is desirable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual text generation is used for advertisements, then customization for different audiences and promotions is possible, but the process becomes inflexible and costly
Solution Approach 1:
The patent implements dynamic text generation where advertisement text is automatically customized based on user attributes, advertiser profiles, and contextual factors. The system transitions from static manual text to dynamic programmatic text generation, allowing real-time adaptation without manual intervention for each advertisement instance.
Solution Approach 2:
The system enables self-service text generation by automatically creating customized advertisement text using natural language models. The system serves itself by generating relevant text based on input parameters without requiring manual writing, thus improving productivity while maintaining customization capability.
2Adaptability or versatility
If custom text is created for each web page and user, then advertisement relevance is maximized, but the expense becomes unjustifiable given the rapid growth of the Internet
Solution Approach 1:
The patent creates a universal text generation system that handles multiple advertisement types, user profiles, and contextual scenarios through a single platform. The natural language model serves multiple functions by generating text for different advertisers, audiences, and promotion types without requiring separate manual processes for each case.
Solution Approach 2:
The system achieves customization by changing parameters such as user attributes, advertiser preferences, and contextual factors rather than creating entirely new text from scratch. This parameter-based approach allows efficient generation of relevant text across many different scenarios without proportionally increasing complexity.
3Productivity
If static text is used in advertisements, then the advertising process is simple and cost-effective, but the utility and potential value of the advertisement are not maximized
Solution Approach 1:
The system performs preliminary text generation based on advertiser profiles and user attributes before the advertisement is displayed. By pre-generating customized text using natural language models, the system prepares relevant content in advance, making the advertisement more useful and effective while maintaining cost-effectiveness through automation.
Data Source
AI summary
Systems, methods, and computer-readable media for dynamically generating text associated with an advertisement are provided. Core text associated with an advertisement is received from an advertiser, as is at least one attribute relevant to the advertiser and/or a user. Based upon the received attribute(s), it is determined whether customization of the core text is desired. If customization is desired, the core text is modified and presented in association with the advertisement. If customization is not desired, the core text is presented in association with the advertisement. In one embodiment, target advertisement placement information may also be utilized to determine whether customization of the core text is desired.