Knowledge Sharing Service Using SNS Relationship Segmentation
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Solution Overview
Problem
Existing social network services (SNSs) are not designed to effectively share professional knowledge and are inadequate for delivering and responding to queries, lacking the functionality to rapidly disseminate queries to reliable answerers within the network.
Innovation Solution
A knowledge sharing service system that utilizes user relationship information from SNSs to query connected users, allowing queries to be shared among contacts based on relationship intimacy levels, and assigns scores to users providing relevant replies, thereby facilitating efficient knowledge sharing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If queries are disseminated widely in SNS network, then the likelihood of obtaining accurate responses increases, but the complexity of managing query distribution and relationship information increases
Solution Approach 1:
The system segments the SNS network into hierarchical levels based on relationship intimacy (e.g., close friends, acquaintances, contacts). Queries are distributed selectively to users at different relationship levels rather than broadcasting to the entire network, thereby maintaining response accuracy while reducing system complexity.
Solution Approach 2:
Different parts of the network receive different treatment based on their relationship characteristics. The system applies localized distribution strategies tailored to each user's relationship profile, matching queries to appropriate relationship levels and reducing unnecessary system-wide complexity.
2Speed
If queries are shared with more users, then the speed of obtaining responses increases, but the loss of control over information distribution increases
Solution Approach 1:
The system dynamically adjusts query distribution based on real-time relationship information and user profiles. It flexibly determines which users receive queries at which relationship levels, enabling fast response times while maintaining precise control over information flow through adaptive, context-aware distribution rules.
Solution Approach 2:
The system implements feedback mechanisms where response outcomes inform future query distribution decisions. By monitoring which relationship levels provide successful responses, the system learns and adjusts distribution patterns, maintaining both speed and control through continuous optimization based on actual performance data.
3Measurement precision
If relationship information is utilized for query distribution, then the relevance of responses increases, but the difficulty of detecting and measuring relationship metrics increases
Solution Approach 1:
The system introduces an intermediary layer that translates complex SNS relationship data into simplified distribution criteria. This mediator processes raw relationship information (interaction history, connection depth, engagement metrics) and converts it into actionable query distribution rules, maintaining high response relevance while reducing the complexity of direct relationship measurement.
4Productivity
If scoring mechanism is implemented for reply contributors, then user participation increases, but the complexity of evaluating and assigning scores increases
Solution Approach 1:
The scoring mechanism operates semi-autonomously using predefined criteria based on query-response matching, user expertise profiles, and relationship relevance. The system automatically evaluates and assigns scores without requiring complex manual intervention, thereby increasing user participation while keeping the scoring system manageable through rule-based automation.
Data Source
AI summary
A knowledge sharing system includes a social network service (SNS) providing server that stores relationship information between a first user and a second user. The knowledge sharing system includes a knowledge sharing service providing server including a query data management unit that stores query data when the query data is transmitted from a first terminal of the first user and stores a query sharing request in association with the query data when the query sharing request is transmitted from a second terminal of the second user, and in the storing of the query sharing request, the query data management unit matches the query sharing request with the query data; and a query data providing unit that provides the query data matched with the query sharing request to a third terminal of a third user, where the third user is connected with the second user in the SNS platform.