Trust-Metric Network for Spam Filtering and Targeted Communication
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Solution Overview
Problem
Existing communication systems face challenges in accurately targeting and filtering communications to prevent unwanted messages, leading to issues like spam and wasted resources for legitimate businesses, as current regulations are not effectively enforced across all communication channels.
Innovation Solution
Implementing trust-metric networks that utilize social network relationships to prioritize and filter communications by determining social distances and affinity groups, allowing senders to target specific recipients and receivers to control the volume and relevance of incoming messages based on trust metrics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If regulations are passed to reduce unwanted communication, then the amount of spam and unsolicited calls is reduced, but enforcement is ineffective across all communication channels and work-arounds emerge
Solution Approach 1:
The patent introduces an intermediary trust-metric system that operates between communication senders and receivers. This intermediary layer calculates trust metrics based on social network relationships and communication history, enabling automated filtering of unwanted communications without requiring external regulation enforcement. The trust-metric acts as a mediator that objectively assesses communication legitimacy based on predefined criteria.
Solution Approach 2:
The system implements feedback mechanisms where communication patterns, user responses, and trust metric calculations continuously inform future communication routing decisions. User feedback on communication relevance and trustworthiness is incorporated into the trust-metric calculations, creating a self-improving system that adapts to emerging spam patterns without requiring external regulatory updates.
2Productivity
If businesses send communications to broad audiences, then potential reach is maximized, but money is wasted on disinterested parties and goodwill is reduced
Solution Approach 1:
The patent applies local quality by segmenting the communication target audience based on trust metrics and social network relationships. Instead of treating all potential recipients uniformly, the system identifies and prioritizes local clusters of trusted contacts and their connections, delivering communications to specific subgroups most likely to be interested while excluding disinterested parties.
Solution Approach 2:
The communication audience is segmented into multiple tiers based on trust metric values and social distance. The system divides the potential recipient population into high-trust segments (direct contacts and close connections), medium-trust segments (distant connections), and low-trust segments (unfamiliar parties), allowing selective communication deployment to optimize both reach and resource efficiency.
3Adaptability or versatility
If keyword purchasing is used for search results, then businesses can target specific search terms, but irrelevant ads appear for unrelated search intents
Solution Approach 1:
The trust-metric system acts as an intermediary layer between keyword-based ad targeting and user exposure. Even when users search for specific terms, the system interposes trust metric evaluation to determine whether the advertised content should be displayed based on the relationship between the user and the advertising entity, filtering out irrelevant ads regardless of keyword matching.
Solution Approach 2:
The advertising display decision is made dynamic by continuously evaluating trust metrics that change based on communication history, user interactions, and social network updates. Rather than static keyword-based ad placement, the system dynamically adjusts ad visibility based on real-time trust assessments, allowing the same keyword search to yield different results at different times based on relationship context.
Data Source
AI summary
A method for a computer system includes receiving a first user communication, determining a first group of users, determining a target number of users, determining whether the first group of users includes the target number of users, and if not, providing the communication to the first group of users, determining a hierarchal mapping of groups of users in response to user memberships, determining a second group of users from the hierarchal mapping, determining a plurality of social network relationship factors for the second group of users with respect to the first user, and providing the communication to at least a subset of users in the second group of users in response to the first plurality of social network relationship factors.