Context-Aware Animation Generation for Ad Displays
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Solution Overview
Problem
Existing computerized graphical advertisement displays lack customization for specific user devices, applications, and publisher contexts, resulting in animations that are not tailored for individual user experiences.
Innovation Solution
A method and system for dynamically generating graphical display source code by altering seed animations based on user device capabilities and context-specific factors, such as layout, time constraints, and user behavior, to select and optimize animations for personalized display.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If animations are customized based on user device capabilities and context-specific factors, then animation relevance and user engagement improve, but system complexity and computational resources required increase
Solution Approach 1:
The system segments the animation generation process into distinct modules: retrieving seed animations from a library, generating candidate animations through systematic variations, scoring candidates based on multiple context factors (device capabilities, user preferences, publisher context), and selecting the optimal animation. This modular segmentation manages complexity by organizing the customization process into manageable, independent components that can be developed and optimized separately.
Solution Approach 2:
The system performs preliminary actions by pre-retrieving seed animations and pre-establishing scoring criteria based on device capabilities and context factors before final animation selection. Candidate animations are generated in advance through systematic variations of seed animations, and their scores are computed beforehand, allowing the system to make informed selection decisions without real-time computational burden during actual display.
2Manufacturing precision
If multiple candidate animations are generated and scored based on context factors, then animation quality and personalization improve, but processing time and computational resources increase
Solution Approach 1:
The system changes parameters systematically by generating candidate animations through controlled variations of seed animation parameters (such as timing, scaling, positioning, and playback speed). By adjusting these parameters in predefined ways, the system creates diverse candidate animations that maintain quality while enabling efficient comparison and selection based on context-specific scoring, thus balancing animation quality with processing efficiency.
3Ease of operation
If animations are tailored to specific user devices and contexts, then user experience and advertising effectiveness improve, but data processing requirements and system resources increase
Solution Approach 1:
The system introduces an intermediary scoring mechanism that mediates between raw context data (device capabilities, user preferences, publisher context) and animation selection. This scoring intermediary processes and synthesizes multiple data factors into a unified evaluation metric, reducing the complexity of direct data processing while enabling personalized animation selection that improves user experience without overwhelming system resources.
Data Source
AI summary
A computer receives a request for graphical display source code for a computerized graphical advertisement display, and retrieves seed animations including a plurality of seed animation features. The computer generates candidate animations based on the one or more seed animations, where the computer alters a first aspect of a seed animation to generate an altered seed animation having a plurality of altered seed animation features and the computer alters a second aspect of the altered seed animation to generate a candidate animation having a plurality of candidate animation features. The computer generates candidate animation scores based upon a context of the advertisement display and the plurality of candidate animation features. The computer selects an animation from the candidate animations based on the candidate animation scores and generates the graphical display source code based on the selected animation, a size of the advertisement display, and display capabilities of the user device.