Template Selection for Content Items Using Context Data
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Solution Overview
Problem
Existing content distribution systems struggle to select the most effective template for content items, such as advertisements, based on user and resource context data, leading to suboptimal performance in terms of user interaction and relevance.
Innovation Solution
The system receives context data from content item requests, identifies eligible templates based on historical performance measures, and selects a template from a template feed that best matches the context data, populating it with relevant content to create a formatted content item.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a single template is used for all content items, then device complexity is reduced, but adaptability to different user contexts and resources deteriorates
Solution Approach 1:
The patent implements a template feed system where a single template can serve multiple functions by being selected and populated based on different context data. The system evaluates multiple templates against context data (user attributes, resource attributes) and selects the most appropriate one, allowing one template structure to adapt to various contexts without requiring separate templates for each scenario.
Solution Approach 2:
The template selection process is dynamic rather than static. The system continuously evaluates context data and selects templates based on current user attributes and resource attributes. This dynamic selection allows the template to adapt to changing contexts without requiring manual intervention or complex pre-configured template variations.
2Adaptability or versatility
If multiple templates are maintained for different contexts, then adaptability to user context improves, but device complexity increases
Solution Approach 1:
The system automatically evaluates context data and selects the most appropriate template without requiring manual intervention. The template feed system self-manages the selection process by comparing context data against template criteria and automatically populating the selected template with relevant content, reducing the complexity of manual template management.
Solution Approach 2:
The system uses context data as feedback to determine which template to select. By continuously evaluating user attributes and resource attributes against template requirements, the system provides feedback-driven template selection that adapts to current conditions without requiring complex pre-programming of all possible scenarios.
3Reliability
If template selection is based on comprehensive context data evaluation, then content relevance improves, but processing time increases
Solution Approach 1:
The system evaluates multiple templates against context data but does not require exhaustive analysis of every possible attribute. Instead, it performs sufficient evaluation to identify the most appropriate template from the feed, accepting that not all attributes need to be fully processed to make an effective selection. This partial action approach maintains relevance while reducing processing time.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting a template for a content item. In one aspect, a method includes receiving a content item request that includes context data. A content item that is eligible to be presented in response to the content item request is identified. A determination is made that the content item includes a template variable that is resolved based on the context data. A template feed including a set of templates is identified based on the template variable. A template is selected from the template feed for the content item. The template can be selected based on the context data. The selected template is populated with content for the content item to create a formatted content item. The formatted content item is provided in response to the content item request.