Semi-supervised Identity Aggregation Using Multi-heuristic Scoring
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Solution Overview
Problem
The fragmentation of personal data across different social media networks makes it difficult to determine if multiple profiles belong to the same individual, leading to inaccurate counting and a lack of practical methods to verify data validity in automated algorithms.
Innovation Solution
A semi-supervised identity aggregation system that analyzes profiles from different social networks to identify matches using multiple heuristics, combining scores from various methods to generate a match score, and allowing for user input to correct false positives or negatives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated algorithms process social media data by traversing the social media graph, then processing speed and efficiency are improved, but measurement precision deteriorates due to inability to correctly recognize multiple profiles belonging to the same person
Solution Approach 1:
The patent segments the profile matching process into multiple independent heuristic components (name matching, email matching, phone number matching, address matching, etc.), each calculating a separate score. These segmented heuristics are then combined to produce an overall match score, allowing the system to maintain high processing speed while improving measurement precision through multi-factor analysis.
Solution Approach 2:
The patent changes the parameter of profile identification from simple exact matching to a probabilistic scoring system. By transforming the matching criterion into a continuous match score based on multiple heuristics, the system can distinguish between strong matches and weak matches, thereby improving measurement precision while maintaining automated processing efficiency.
2Device complexity
If multiple profiles are treated as separate individuals in automated counting, then processing complexity is reduced, but measurement precision deteriorates due to inaccurate counting of social media fans
Solution Approach 1:
The patent performs preliminary profile aggregation and matching before the actual counting process. By pre-processing the data to identify and merge duplicate profiles using multiple heuristics, the system ensures that subsequent counting operations are performed on deduplicated data, thereby improving counting accuracy without significantly increasing overall system complexity.
3Ease of operation
If conventional techniques are used to process social media information, then ease of operation is maintained, but reliability deteriorates due to lack of practical methods to verify data validity
Solution Approach 1:
The patent implements a feedback mechanism where match scores from multiple heuristics are continuously evaluated and combined. The system provides feedback on the confidence level of profile matches, allowing operators to review and validate uncertain matches. This feedback loop improves reliability by enabling verification of data validity while maintaining ease of operation through automated scoring and selective manual review.
Data Source
AI summary
User profiles can be analyzed to identify profiles matching to the same identity. For example, profiles from different social network systems are analyzed to determine if the profiles are associated with the same user of the social network systems. Multiple heuristics may be calculated using different algorithms. The calculated heuristics may then be combined to generate a match score that indicates whether two profiles match.