Generative AI Web Content Generation with Iterative Query Refinement
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Solution Overview
Problem
Current web content generation methods for fast-moving industries like travel are inefficient, leading to resource-intensive server-side rendering, outdated information, and the need for multiple websites, resulting in high storage and transmission requirements.
Innovation Solution
A method utilizing a generative AI system to efficiently generate web content by iteratively refining queries based on required and optimization criteria, allowing for the creation of relevant, accurate, and up-to-date content in multiple languages, while minimizing processing power and storage needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If server-side rendering techniques are used to dynamically generate content on request, then content relevance and accuracy are improved, but server processing time and user experience are degraded due to bottlenecks
Solution Approach 1:
The patent pre-generates web content at scheduled intervals before users request it. The generative AI system creates and stores content in advance based on predicted user needs and search queries, so when a user requests content, it is already available and can be served immediately without real-time server rendering delays.
Solution Approach 2:
The patent implements a hybrid approach where the system dynamically adjusts between pre-generated static content and on-demand generative AI content. The system monitors content freshness requirements and user behavior patterns to determine which content should be pre-generated and which should be generated on request, optimizing the balance between speed and accuracy.
2Quantity of substance
If traditional web content generation methods are used, then storage and transmission resources are consumed, but content relevance to specific user needs is reduced due to general information design
Solution Approach 1:
The patent applies local quality by personalizing web content based on individual user profiles, search history, and preferences. The generative AI system creates customized content for each user rather than serving generic information, ensuring that the content volume is optimized for each user's specific needs and that information relevance is maximized.
Solution Approach 2:
The patent changes the parameters of content generation by using generative AI to dynamically adjust content characteristics such as language, tone, depth, and focus based on user attributes. This allows the system to serve appropriate content volume and relevance by modifying generation parameters rather than using fixed templates.
3Measurement precision
If companies maintain web content in multiple languages manually, then translation accuracy is improved, but time and technical resources required are significantly increased
Solution Approach 1:
The patent implements self-service by enabling the generative AI system to automatically generate and translate content in multiple languages without human intervention. The system maintains translation quality through continuous learning from user feedback and interactions, allowing it to serve multiple languages autonomously while keeping content updated in real-time.
Solution Approach 2:
The patent replaces the mechanical system of manual translation with an automated generative AI system that uses natural language processing and machine translation capabilities. This substitution eliminates the time-consuming manual translation process while maintaining or improving translation quality through the AI's ability to learn from context and user feedback.
4Use of energy by moving object
If web content is kept brief and static to reduce processing requirements, then server resource consumption is reduced, but search engine ranking and visibility are degraded
Solution Approach 1:
The patent implements periodic action by scheduling regular updates of web content at optimized intervals. The system generates and updates content periodically based on freshness requirements and search engine optimization needs, maintaining adequate content volume for visibility while avoiding continuous processing that would consume excessive server resources.
Data Source
AI summary
Methods, systems, and computer program products for providing web content for a plurality of users. The method includes inputting a query to a generative AI system. The query includes a plurality of keywords including a location identifier. An output is received from the generative AI system based on the query. The output is analysed to determine whether the content of the output meets at least one required criterion and whether the output meets at least one optimization criterion. A revised query is then formed based on the results of the analysis against the required criterion and against the optimization criterion, and the revised query is input to the generative AI system with at least one additional keyword. A revised output of the generated web content is received from the generative AI system and stored at a server for retrieval by a user.