Entity Collection-Based Sponsored Content Presentation in Search
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Solution Overview
Problem
Current content presentation systems on the Internet fail to effectively integrate sponsored content with search results based on specific entity collections, leading to suboptimal user engagement and conversion rates.
Innovation Solution
A computer-implemented method that allows content sponsors to specify entity collections with common characteristics, enabling the presentation of relevant sponsored content items alongside search results, using an entity engine to identify eligible content items and a related content identification engine to display them prominently within the search results.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If sponsored content is integrated with search results based on entity collections, then user engagement and conversion rates improve, but system complexity increases
Solution Approach 1:
The system segments content selection by dividing entities into distinct collections based on common characteristics. Each entity collection serves as an independent segment that can be matched with relevant sponsored content, allowing the complex problem of content selection to be broken down into manageable segments that improve engagement without overwhelming system complexity
Solution Approach 2:
Entity collections serve as intermediary structures between raw search queries and sponsored content selection. The system introduces entity collections as a mediating layer that organizes entities with common characteristics, enabling more effective content matching while managing complexity through this intermediate organizational structure
2Productivity
If sponsored content is displayed among related entities, then conversion rates increase, but content selection precision requirements increase
Solution Approach 1:
The system applies local quality by creating entity collections where entities share specific common characteristics. This allows content selection precision to be tailored to local contexts - each entity collection can be matched with content that has precise relevance to those specific characteristics, improving conversion rates without requiring uniform high precision across all content selections
Solution Approach 2:
The system changes the parameter of content selection from direct query-matching to entity-collection-based matching. By transforming the selection criteria from raw search terms to structured entity collections with defined characteristics, the system improves conversion precision while managing the complexity of content selection through parameter transformation
Data Source
AI summary
Methods, systems, and apparatus include computer programs encoded on a computer-readable storage medium, including a method for providing content. An indication is received from a content sponsor of a first collection of entities, sharing common characteristics, to be used for selection criteria for presenting a first content item. References to the first content item and selection criteria are stored. A query is received including terms or phrases associated with a first entity. It is determined that the first entity is included in the first collection of entities, wherein the terms or phrases do not include the first collection. Eligible content items are identified, each being associated with selection criteria including criteria specifying the first collection of entities. At least a portion of the first collection of entities is provided for presentation along with search results, including providing one or more of the eligible content items and the first content item.