Content Selection Server Interest-Based Delivery
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Solution Overview
Problem
Users often have to proactively seek out online content of interest, as existing systems lack the ability to dynamically provide content based on a user's potential relevance to their interests without explicit user action.
Innovation Solution
A computerized method and system that analyzes user history data to identify interest categories and uses custom selection rules to select and provide relevant content to users, allowing content providers to specify rules based on interest categories and identifier lists, and conducts auctions to determine content eligibility.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users proactively search for content using search engines, then they can find content of interest, but they must spend time and effort to locate relevant content manually
Solution Approach 1:
The system enables content to serve itself by automatically analyzing user history data and applying selection rules to deliver relevant content without user intervention. The content selection server autonomously processes user behavior data, evaluates content against selection criteria, and provides personalized content recommendations, eliminating the need for users to manually search through search results.
2Reliability
If content is provided based on user history analysis, then content relevance to user interests is improved, but the system complexity increases due to data processing and rule evaluation requirements
Solution Approach 1:
The system segments the content selection process into distinct functional components: history data collection, interest category identification, selection rule evaluation, and content delivery. By dividing the complex task into separate modules within the content selection server, each handling a specific aspect of content personalization, the system manages complexity while maintaining high content relevance through coordinated operation of these segmented functions.
3Adaptability or versatility
If custom selection rules are implemented for content providers, then targeted content delivery to specific user groups is enabled, but the rule management and evaluation process becomes more complex
Solution Approach 1:
The system manages rule complexity by parameterizing selection rules with standardized fields such as interest categories, user demographics, and content attributes. Content providers can define targeting criteria using these standardized parameters rather than complex custom logic, and the system automatically evaluates rules by comparing user profile parameters against rule parameters, simplifying both rule creation and evaluation while maintaining sophisticated targeting capabilities.
Data Source
AI summary
Systems and methods for providing online content include evaluating a custom selection rule specified by a content provider. The custom selection rule may be used to control whether content from the provider is eligible for selection by a content selection service. The content selection rule may include one or more logical operators, a selected interest category and/or a selected list of one or more client identifiers.