Dynamic Content-Sharing Profiles from Common Activity Data
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Solution Overview
Problem
Conventional content sharing platforms lack dynamic profile generation capabilities, failing to incorporate relationship information, common activities, compatibility, and location-based features, leading to inefficient user interaction and content sharing.
Innovation Solution
A system that generates user profiles dynamically by incorporating relationship information, common activity data, compatibility indicators, and location-based features, allowing users to create and share media content with enhanced interaction and access to favorite items.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional content sharing platforms use static profile information, then the system complexity is low, but user engagement and interaction efficiency deteriorate
Solution Approach 1:
The patent implements dynamic profile generation that automatically updates profile information based on user activities, relationships, and interactions. The profile transitions from a static data structure to a dynamic representation that evolves with user behavior, incorporating real-time activity data, relationship changes, and interaction patterns without requiring manual user input.
Solution Approach 2:
The system enables self-updating profiles where the platform automatically collects, processes, and integrates user-generated content and interaction data to populate profile fields. The profile generation process operates autonomously by monitoring user activities across the platform and synthesizing this information into comprehensive profile representations without external intervention.
2Loss of information
If the platform incorporates comprehensive relationship information and common activities in profiles, then user engagement improves, but information processing time increases
Solution Approach 1:
The system pre-processes and stores user activity data, relationship information, and interaction patterns in structured formats as they are generated on the platform. This preliminary organization of data enables rapid profile assembly when needed, as the information is already categorized and ready for integration rather than requiring real-time collection and processing.
Solution Approach 2:
The patent replaces traditional mechanical data collection and processing methods with automated computational systems that continuously monitor, aggregate, and analyze user behaviors. Machine learning algorithms and data processing engines substitute manual or batch-processing approaches, enabling real-time or near-real-time profile updates without proportionally increasing processing time.
3Productivity
If the system generates detailed profiles with compatibility indicators and location-based features, then content sharing efficiency improves, but computational resources consumed increase
Solution Approach 1:
The system generates profile details and compatibility indicators selectively based on user needs, context, and interaction patterns. Rather than computing all possible profile attributes uniformly, the platform calculates and displays only the most relevant information for each specific interaction scenario, reducing unnecessary computational overhead while maintaining sharing efficiency.
Solution Approach 2:
The patent dynamically adjusts profile generation parameters such as detail depth, compatibility calculation intensity, and location-based feature activation based on user preferences, device capabilities, and interaction context. The system modifies computational parameters in real-time to optimize the balance between profile comprehensiveness and resource consumption, scaling processing intensity to match actual needs.
Data Source
AI summary
Systems and methods are provided receiving, from a computing device associated with a first user of a content sharing platform, a request to access a second user profile associated with a second user in the content sharing platform, accessing activity data related to both the first user and the second user in the content sharing platform, determining common activity data to both the first user and the second user, wherein the common activity data comprises at least one media content item generated by the second user that was viewed or saved by the first user, or one or more datum saved by the first user from a communication received from the second user, and generating second user profile data comprising the common activity data related to both the first user and the second user in the content sharing platform as part of the second user profile.