Web Page Ad Placement Using Region-Specific Ranking Models
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Solution Overview
Problem
Current web search engines face challenges in optimizing the placement of advertisements on web pages to maximize user selection and revenue, as existing methods do not account for varying user preferences across different regions of a web page.
Innovation Solution
A system and method that rank advertisements separately for each region of a web page using different models to select the highest-ranked ads for placement, based on the probability of user selection, enhancing user experience and revenue generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If advertisements are placed using a single ranking model for all regions, then the system complexity is low, but the user selection probability and advertising revenue are suboptimal
Solution Approach 1:
The patent divides the web page into multiple distinct regions (e.g., top, side, bottom) and applies separate ranking models to each region. This segmentation allows the system to capture region-specific user preferences and behaviors, thereby improving advertising revenue through more targeted ad placement while managing complexity by organizing the system into modular region-handling components.
Solution Approach 2:
The patent implements local quality by using different ranking models optimized for specific regions rather than a single universal model. Each region receives ads ranked according to its unique characteristics and user interaction patterns, improving the overall effectiveness of ad placement and maximizing revenue from each region's potential.
2Reliability
If advertisements are ranked separately for each region using different models, then the user selection likelihood increases, but the computational complexity and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing region-specific ranking models based on historical data and user behavior patterns. When ads need to be placed, the system retrieves these pre-computed models and applies them to the current ad inventory, significantly reducing real-time processing time while maintaining high user selection likelihood through region-optimized ranking.
3Productivity
If advertisements are ranked separately for each region using different models, then the advertising revenue increases, but the device complexity increases
Solution Approach 1:
The patent divides the web page into multiple distinct regions (e.g., top, side, bottom) and applies separate ranking models to each region. This segmentation allows the system to capture region-specific user preferences and behaviors, thereby improving advertising revenue through more targeted ad placement while managing complexity by organizing the system into modular region-handling components.
Solution Approach 2:
The patent implements a centralized ad selection module that serves multiple regions with different ranking models. This universal module handles ad ranking and selection for all regions, reducing overall system architecture complexity by consolidating the ad selection logic in a single multi-functional component rather than distributing it across multiple specialized systems.
Data Source
AI summary
A system and method is described herein that selects advertisements for two or more regions of a web page based on rankings of the advertisements generated using different models. By ranking advertisements separately for each region of a web page, and choosing highest ranked advertisements for each region, advertisements can be selectively chosen such that a user is more likely to select an advertisement in each region of the web page. As a result, the user experience can be enhanced and the advertising revenue can be correspondingly increased.