Interactive Content Modification via Semantic Information Analysis
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Solution Overview
Problem
Current artificial intelligence technologies require users to repeatedly modify input to achieve desired content generation, leading to a poor user experience due to inefficient interaction processes.
Innovation Solution
An interactive method and device that obtain and modify semantic information of display content based on user input, allowing for accurate and efficient modification of generated content without extensive user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If users repeatedly modify input content to achieve desired generation results, then the accuracy of generated content can be improved, but the interaction time and user effort increase significantly
Solution Approach 1:
The system performs preliminary action by automatically generating multiple candidate content variations and pre-calculating their semantic information before user review. This allows the system to proactively prepare multiple options based on the initial input, so users don't need to repeatedly modify the input - they can simply select from pre-generated candidates that already cover various possible desired outcomes.
Solution Approach 2:
The system implements feedback by displaying multiple candidate content variations to users and collecting their selections or preferences. This feedback mechanism allows the system to learn from user choices and automatically adjust subsequent content generation, reducing the need for users to manually re-input or repeatedly modify content while still achieving high accuracy.
2Manufacturing precision
If users repeatedly modify input content to achieve desired generation results, then the quality of generated content can be improved, but the number of interaction operations increases
Solution Approach 1:
The system applies self-service by automatically generating multiple candidate content variations and performing semantic analysis without requiring user intervention. The system serves itself by autonomously creating options, evaluating them semantically, and presenting curated selections to users, thereby reducing interaction complexity while maintaining high content quality through automated refinement processes.
Solution Approach 2:
The system performs preliminary action by pre-generating multiple candidate content variations and pre-evaluating their semantic information before user review. This allows the system to proactively prepare high-quality options that users can simply select from, eliminating the need for users to perform multiple modification operations while still achieving desired content quality.
3Device complexity
If the system generates content based on single input without semantic modification capability, then the device complexity is reduced, but the adaptability to user needs deteriorates
Solution Approach 1:
The system applies segmentation by separating the content generation process into distinct modules: an initial content generation module that maintains simplicity, and a semantic information processing module that handles adaptability. The semantic information module is further segmented into candidate generation, semantic analysis, and selection recommendation components. This modular segmentation allows the core system to remain simple while adding adaptability through optional semantic processing layers.
Solution Approach 2:
The system introduces semantic information as an intermediary between user input and final content generation. This intermediary layer processes the relationship between input and output, enabling the system to adapt to user needs without fundamentally complicating the core generation architecture. The semantic information acts as a bridge that translates user intent into optimized content variations.
Data Source
AI summary
An interactive method includes: obtaining to-be-modified display content in a display content, the display content being generated based on a first input content input by a user; obtaining semantic information of the to-be-modified display content; obtaining a second input content input by the user, and based on the second input content, modifying the semantic information of the to-be-modified display content to obtain modified semantic information; and based on the modified semantic information, modifying the display content to obtain modified display content.