Social Network Content Personalization via Interest Inference
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Solution Overview
Problem
Social networking systems face challenges in personalizing user interactions and content delivery based on inferred interests and unviewed content, with limitations in integrating third-party system content and efficiently presenting relevant information to users.
Innovation Solution
The system analyzes user interactions and content objects to infer interests, modifies user pages with relevant content, and provides curated pages with unviewed content from friends, utilizing third-party system data while ensuring privacy settings are respected.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the system integrates third-party system content and analyzes user interactions to infer interests, then content personalization and user engagement are improved, but system complexity and data processing requirements increase
Solution Approach 1:
The system divides the complex task of content personalization into separate modules: third-party content integration module, user interaction analysis module, interest inference module, and content delivery module. Each module handles a specific aspect of the personalization process, making the overall system more manageable and maintainable while achieving high adaptability
Solution Approach 2:
The patent introduces intermediary components such as interest inference engines that act as mediators between raw user interaction data and personalized content delivery. These intermediaries process and transform data between different system components, reducing direct complexity while enabling sophisticated personalization
2Productivity
If the system delivers personalized content and curates unviewed content from friends, then user engagement and content discovery are improved, but information processing and storage requirements increase
Solution Approach 1:
The system performs preliminary actions by pre-analyzing user interactions and pre-infering interests before content delivery requests. User profiles and interest models are built in advance, allowing the system to quickly retrieve and deliver personalized content without processing all raw data in real-time, thus reducing instantaneous data processing volume while maintaining high user engagement
Solution Approach 2:
The patent applies local quality by curating content specifically for each user based on their inferred interests and viewing history. Instead of processing and delivering all available content uniformly, the system selectively processes and delivers only the most relevant unviewed content from friends and connections, reducing overall data processing volume while improving engagement through targeted content delivery
3Measurement precision
If the system tracks post viewership and analyzes user interactions, then content relevance and personalization are improved, but user privacy concerns and security requirements increase
Solution Approach 1:
The system changes parameters by processing and aggregating user interaction data into anonymized interest profiles rather than storing or processing individual detailed interaction records. This transformation maintains measurement precision for content relevance while reducing privacy concerns by removing personally identifiable information from the processed data
Solution Approach 2:
The patent extracts only the essential information needed for personalization (such as interaction patterns and content preferences) while leaving out sensitive personal details. The system separates viewership tracking data from user identity data, processing only the extracted behavioral patterns needed for content relevance while minimizing privacy exposure
Data Source
AI summary
In one embodiment, a method includes identifying one or more first users of a social-networking system associated with one or more content objects not previously viewed by a second user. The identification is based at least in part on an affinity of the second user for the first users and the first users are connected to the second user on a social graph. The method also includes providing, for display on a client device of the second user, information indicating that one or more of the identified first users has content objects not previously viewed by the second user; receiving an input selecting one of the identified first users; and providing, for display on the client device, an online page comprising content associated with the selected first user that incorporates one or more of the content objects not previously viewed by the second user.