Communication Server Alliance Filtering
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Solution Overview
Problem
Existing social network and professional network systems lack the ability to effectively manage and filter digital communications based on the type and strength of relationships between user accounts, leading to inefficient contact management and decision-making processes.
Innovation Solution
A communication management server that creates and stores digital records of alliances between user accounts, allowing for the filtering of messages and content based on relationship strengths, enabling users to form alliances and share relevant information to expand their networks efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If existing social network systems use binary linkage to manage connections, then the system structure is simple, but the ability to filter and manage communications based on relationship strength is limited
Solution Approach 1:
The patent transforms the binary connection model into a multi-dimensional relationship model by introducing relationship strength as a variable parameter. Connections are now characterized by multiple attributes including strength levels (weak, medium, strong), relationship types (professional, personal, acquaintance), and interaction frequency, allowing for nuanced filtering and management of communications based on these parameters
2Adaptability or versatility
If the system stores detailed relationship information for all connections, then communication filtering capability is improved, but network traffic and data storage requirements increase
Solution Approach 1:
The patent implements selective data collection and storage by associating relationship attributes only with specific connection pairs rather than maintaining comprehensive relationship data for all users. The system stores relationship strength, type, and interaction metrics locally for each alliance pair, enabling targeted filtering without the overhead of global relationship databases
Solution Approach 2:
The system pre-calculates and stores relationship attributes and alliance data before communications occur. By establishing alliances and computing relationship metrics in advance, the system prepares filtering criteria beforehand, reducing the need for real-time computation and minimizing network traffic during actual communication sessions
3Measurement precision
If users manually manage their contact networks, then relationship information accuracy is maintained, but time consumption increases
Solution Approach 1:
The system automatically computes relationship strength and attributes by analyzing interaction patterns between users. Metrics such as communication frequency, message length, and interaction recency are collected and processed automatically to generate relationship profiles without requiring manual user input, while maintaining accuracy through objective behavioral data
Solution Approach 2:
The system continuously monitors communication patterns and updates relationship attributes in real-time based on observed interactions. As users communicate, the system feeds back relationship strength adjustments and alliance status changes, automatically refining relationship information accuracy through ongoing behavioral feedback without requiring manual re-evaluation
Data Source
AI summary
A communication management server computer (“server”) and related methods are disclosed to create and store digital records representing alliances between user accounts and to use the alliance records in filtering messages or other content and/or determining attributes of messages or content for display. The server allows two electronic devices associated with two user accounts to establish an alliance, where each of the two user accounts offers a set of digital communications for exploration of relationships and agrees to share certain types of information regarding the relationships with the other user account.