Event Suggestion Relevance Scoring for Social Networks
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Social networking systems face challenges in notifying users of events without overwhelming them with information, especially with large user bases.
Innovation Solution
A social networking system suggests events to users based on their interactions, connections, availability, proximity, and affinity with other attendees, using a relevance score calculated by the system to select and present relevant events, along with invitations to facilitate user participation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the social networking system notifies each user of all events generated by users and entities, then users receive complete event information, but users are overloaded with excessive information
Solution Approach 1:
The system extracts and selects only the most relevant events from the complete event dataset based on user profile attributes, connection data, and interaction history. This filtering process removes irrelevant events while retaining important ones, thus preventing information overload while maintaining information completeness for relevant events.
Solution Approach 2:
The system applies different selection criteria and relevance thresholds tailored to each user's specific profile, connections, and interaction patterns. This personalized approach ensures that each user receives a customized subset of events that is relevant to their local context and interests, rather than a uniform notification list for all users.
2Reliability
If the social networking system sends event notifications to all users, then all users are notified of events, but the system complexity and processing requirements increase
Solution Approach 1:
The system pre-computes user profiles, connection graphs, and interaction patterns before event notification is needed. By maintaining pre-processed data structures including user attributes, connection data, and interaction history, the system can quickly filter and select relevant events without performing complex real-time analysis when events occur, thus reducing processing complexity while maintaining notification reliability.
3Measurement precision
If the system uses multiple selection criteria to filter events, then event relevance to users improves, but the computational requirements and processing time increase
Solution Approach 1:
The system segments the event filtering process into multiple independent stages: first filtering by basic criteria (user attributes, connection data), then by interaction history, and finally by relevance scoring. This segmentation allows the system to apply multiple selection criteria efficiently by breaking down the complex filtering task into manageable steps, reducing overall processing time while maintaining high relevance accuracy.
Data Source
AI summary
A social networking system suggests events for a target user based on stored data in the social networking system related to the target user and to events. The social networking system may suggest events based on the target user's affinity for, connections with, or interactions with objects in the social networking system connected to or otherwise associated with the events. For example, an event is suggested to a target user if users connected to the target user already accepted an invitation to the event. As another example, an event organized by a particular entity is suggested to the target user because of interactions between the target user and other content provided by the entity. Invitations to suggested events may be presented to the target user via a client device, allowing the target user to easily join a suggested event.