Social Message Pruning via Generation Segmentation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Social networking systems face challenges in managing and pruning large volumes of correspondence, leading to inefficiencies and resource wastage due to the need for selective deletion or archiving of messages, especially as users accumulate a significant number of messages over time.
Innovation Solution
A dynamic pruning program that analyzes correspondence within a social networking system based on uniqueness and relationship criteria, identifying key topics and establishing generation links to suggest which messages can be pruned, thereby reducing the volume of messages and organizing them into relevant groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If users accumulate more messages in their activity streams, then the volume of correspondence increases, but the efficiency of data processing and resource utilization deteriorates
Solution Approach 1:
The patent segments messages into different generations based on their relationship to seed messages. First-generation messages are directly related to seed messages, while second-generation messages are related to first-generation messages. This segmentation allows the system to process and prune messages in hierarchical batches, improving processing efficiency by handling smaller, more manageable subsets rather than processing all messages simultaneously.
Solution Approach 2:
The patent performs preliminary analysis by identifying seed messages and establishing generation links before actual pruning occurs. The system pre-computes relationships between messages and organizes them into generations, so that when pruning is needed, the structure is already in place. This preliminary organization significantly reduces the computational overhead during the pruning operation itself.
2Measurement precision
If the system analyzes all correspondence to determine relevance, then the accuracy of message selection improves, but the time required for analysis increases
Solution Approach 1:
The patent divides the correspondence into generations based on their relationship to seed messages. By processing messages generation by generation rather than analyzing all messages simultaneously, the system achieves high accuracy in relevance determination while reducing total analysis time. Each generation can be analyzed independently using the same criteria, maintaining precision while scaling time efficiency.
Solution Approach 2:
The patent implements a dynamic pruning approach where the analysis criteria and generation boundaries can be adjusted based on system needs. The generation link establishment and pruning thresholds are configurable, allowing the system to adapt to different accuracy-time requirements. This dynamic adjustment enables optimization of the balance between measurement precision and time loss based on specific operational contexts.
3Loss of energy
If the system prunes messages aggressively to reduce volume, then resource conservation improves, but the loss of potentially useful information increases
Solution Approach 1:
The patent segments messages into multiple generations, allowing selective pruning at different levels. First-generation messages have the strongest relationship to seed messages and are retained with higher priority, while second-generation messages can be more aggressively pruned. This segmented approach enables resource conservation through selective deletion while maintaining high retention accuracy for the most relevant messages.
Solution Approach 2:
The patent establishes a feedback mechanism where the pruning decisions are based on analyzed relationships between messages and seed messages. The generation link analysis provides feedback about message relevance, allowing the system to prune messages that are clearly less relevant while retaining those with stronger connections. This feedback-driven approach optimizes the balance between resource conservation and information retention.
Data Source
AI summary
Correspondences in a social networking system are analyzed to determine at least one topic. An activity stream with the at least one topic is analyzed. A target audience for the activity steam is identified. The activity stream is analyzed according to a uniqueness and a relationship criteria to form an assessment. The assessment is analyzed to a predetermined action criteria. Performing an action responsive to determining the assessment satisfies the predetermined action criteria.