Dynamic Weight Assignment for Contextual Ad Placement
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Solution Overview
Problem
Probabilistic mixed-content page layout models are not well-equipped to accommodate the placement of contextual advertisements on pages alongside text blocks and images, as they do not account for the dynamic relatedness of advertisements to text blocks, and advertisements cannot be resized due to specific ad size constraints.
Innovation Solution
A modified probabilistic mixed-content page layout model that takes into account the dynamic relatedness of contextual advertisements to text blocks by assigning dynamic weights, allowing for optimal placement without user interaction, while maintaining the static weights for images and ensuring advertisements are not resized.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a traditional probabilistic mixed-content page layout model is used, then the layout process is simple and fast, but it cannot accommodate contextual advertisements with dynamic relatedness to text blocks
Solution Approach 1:
The patent applies dynamics by introducing dynamic weights for contextual advertisements that can change based on their relatedness to different text blocks. Unlike static image weights, advertisement weights are adjusted dynamically according to the specific text block they are placed near, allowing the model to adapt to varying contextual relevance while maintaining a unified probabilistic framework.
Solution Approach 2:
The patent implements local quality by assigning different weight values to different advertisement-text block pairs based on their specific relatedness. Each contextual advertisement receives a tailored weight depending on its relevance to the surrounding text, rather than applying a uniform weight across all advertisements. This localized adjustment enables precise control over advertisement placement quality.
2Manufacturing precision
If contextual advertisements are placed using static weights like images, then the model remains simple, but the dynamic relatedness between advertisements and text blocks is not accounted for
Solution Approach 1:
The system transitions from static to dynamic weight assignment for contextual advertisements. The weight of each advertisement is determined dynamically based on its relatedness to the specific text block it accompanies, allowing the placement precision to adapt to contextual relevance without requiring a completely new model architecture.
Solution Approach 2:
The patent changes the parameter of advertisement weight from a fixed static value to a dynamic value that varies based on contextual relatedness. This parameter change enables the system to achieve higher placement precision by adjusting weights according to the specific advertisement-text block relationship, while the underlying model structure remains consistent.
3Area of stationary object
If advertisements are allowed to be resized to fit layout spaces, then space utilization improves, but advertisement quality and advertiser specifications are compromised
Solution Approach 1:
The patent segments the page layout into distinct regions that accommodate advertisements of fixed sizes. By creating specific advertisement placement zones within the probabilistic framework, the system can maintain proper spacing and sizing for each advertisement without forcing resizing, while still achieving effective space utilization through optimized regional allocation.
Solution Approach 2:
The system applies local quality by treating advertisement regions with different constraints compared to text and image regions. Advertisement areas maintain fixed dimensions to preserve quality and specification compliance, while the surrounding layout adapts locally to accommodate these fixed-size elements, achieving overall space efficiency without compromising advertisement integrity.
4Extent of automation
If manual layout design is used to achieve aesthetic quality, then the aesthetic appeal is high, but the productivity and automation level are low
Solution Approach 1:
The system implements self-service by enabling automatic advertisement placement through the probabilistic model with dynamic weights. The model autonomously determines optimal advertisement positions based on contextual relatedness and aesthetic considerations, eliminating the need for manual intervention while maintaining high layout quality through algorithmic optimization of placement decisions.
Solution Approach 2:
The patent changes the operational parameters of the layout model to include dynamic advertisement weights and aesthetic quality metrics. These parameter changes enable the automated system to make intelligent placement decisions that replicate manual design quality, achieving both high automation and aesthetic precision through optimized parameter interactions within the probabilistic framework.
Data Source
AI summary
One or more text blocks, one or more images, and one or more contextual advertisements related to the text blocks are input into a mixed-content page layout model. One or more pages are generated by the mixed-content page layout model such that the text blocks, the images, and the contextual advertisements are displayed on the pages. For each contextual advertisement, a dynamic weight to a particular text block is determined. The mixed-content page layout model uses the dynamic weight for a contextual advertisement in determining where the advertisement is displayed within the pages in relation to the particular text block.