Social Network Notification Personalization via Third-Party Action Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Social-networking systems face challenges in sending personalized notifications to users based on their actions on third-party websites, as existing methods lack the ability to effectively correlate user behavior across different platforms and environments.
Innovation Solution
A method that involves receiving information about user actions on third-party websites, determining relevant parameters, and sending targeted notifications by correlating these parameters with user behavior patterns, allowing for personalized content delivery based on user preferences and habits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the social-networking system sends notifications to users based on their actions on third-party websites, then user engagement and personalization are improved, but the complexity of correlating user behavior across different platforms increases
Solution Approach 1:
The patent employs an intermediary correlation system that acts as a mediator between third-party websites and the social-networking system. This intermediary component receives action data from external platforms, processes it through parameter determination and correlation algorithms, and then generates personalized notifications. The intermediary approach isolates the complexity within a dedicated module rather than分散 across the entire system, making the personalization capability achievable without overwhelming system-wide complexity.
Solution Approach 2:
The notification system is segmented into distinct functional modules: action reception module, parameter determination module, correlation analysis module, and notification generation module. Each module handles a specific aspect of the personalization process, allowing the system to manage complexity through functional decomposition while maintaining the ability to deliver personalized notifications across multiple third-party platforms.
2Loss of information
If the system correlates multiple parameters with user behavior patterns across different platforms, then notification relevance is improved, but the difficulty of detecting and measuring user actions increases
Solution Approach 1:
The correlation system serves as an intermediary that standardizes the collection and measurement of user actions across different third-party platforms. It establishes a unified framework for detecting and measuring diverse user behaviors, converting platform-specific action data into standardized parameters that can be consistently correlated and analyzed for notification relevance.
Solution Approach 2:
The system transforms raw user action data from various platforms into standardized parameters through parameter determination. This parameter transformation process converts diverse action types (clicks, purchases, views) into a common parameter framework, making them measurable and correlatable across different platforms while preserving the essential information needed for notification relevance.
3Quantity of substance
If the social-networking system integrates data from third-party websites, then the quantity of user information available for personalization increases, but the loss of information during cross-platform correlation increases
Solution Approach 1:
The system creates standardized parameter copies of raw user action data from third-party platforms. Instead of directly processing diverse original data formats, it generates standardized parameter representations that preserve the essential information needed for correlation while reducing data loss during the integration process. This copying approach maintains information integrity across platform boundaries.
Solution Approach 2:
The parameter determination process transforms raw action data into standardized parameters that are optimized for correlation analysis. This parameter transformation maintains the critical information needed for personalization while converting diverse data formats into a unified structure, thereby reducing information loss during cross-platform data integration and correlation.
Data Source
AI summary
In one embodiment, a method includes sending notifications to one or more users of a social-networking system. Information may be received regarding actions taken by the users of the social-networking system. The information may include parameters associated with each of the actions taken by the users. The method further includes determining correlations between the parameters and the users, and sending notifications to the users of the social-networking system based on the determined correlations.