Centralized Text Messaging Control for Cross-Network Opt-Out Enforcement
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Solution Overview
Problem
Conventional systems for managing phone-based text communications lack fine-grained control for recipients, allowing limited opt-in/opt-out options and rely on originating entities to comply with user actions, leading to potential non-compliance and privacy issues.
Innovation Solution
A centralized text communication management system that enables recipients to take granular actions through customizable links, collects and analyzes recipient action data, and uses machine learning to enforce opt-in/opt-out decisions across entities, independent of the originating entity's compliance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional systems allow limited opt-in/opt-out options and rely on originating entities to comply, then system simplicity is maintained, but recipient control and privacy protection are insufficient
Solution Approach 1:
The patent introduces a centralized management system that acts as an intermediary between originating entities and recipients. This system receives opt-in/opt-out actions from recipients, enforces these decisions across the network, and provides fine-grained control over communication preferences. The intermediary handles the complexity of enforcement and compliance tracking, thereby improving recipient control without requiring individual devices to become overly complex.
Solution Approach 2:
The patent segments communication management into distinct functional components: recipient action initiation, action enforcement, compliance monitoring, and machine learning-based prediction. This segmentation allows each component to specialize in specific tasks, improving overall system efficiency and recipient control while distributing complexity across multiple specialized modules rather than concentrating it in a single complex system.
2Reliability
If centralized enforcement and machine learning analysis are implemented, then compliance and privacy protection are improved, but system complexity and processing requirements increase
Solution Approach 1:
The patent implements machine learning models that perform preliminary analysis of communication patterns and predict potential compliance issues before they occur. By analyzing historical data and identifying trends in advance, the system can proactively enforce compliance decisions and prevent non-compliant communications, thereby improving reliability without requiring complex real-time intervention mechanisms for every communication event.
Solution Approach 2:
The system incorporates feedback loops where machine learning models continuously analyze enforcement outcomes and compliance data, then adjust their predictions and enforcement strategies accordingly. This feedback mechanism improves compliance enforcement reliability over time by learning from past decisions and outcomes, while the automated nature of the feedback processing avoids adding significant architectural complexity.
3Measurement precision
If fine-grained recipient actions are enabled, then communication management precision is improved, but data processing and analysis requirements increase
Solution Approach 1:
The patent extracts and isolates the data processing and machine learning analysis functions into a centralized cloud-based infrastructure, separating them from individual recipient devices. This extraction allows fine-grained action tracking and sophisticated data analysis to occur in high-performance server environments rather than resource-constrained mobile devices, thereby achieving high measurement precision without imposing excessive data processing burdens on user devices.
Data Source
AI summary
A text communication management system is provided that receives, analyzes, and enforces recipient actions regarding phone-based text communications. The text communication management system can obtain recipient action data regarding a recipient's action with respect to a particular text communication, and enforce the recipient action with respect to future text communications. The management system can also or alternatively analyze the recipient action data in connection with recipient action data from multiple other recipients to generate a model for use in determining whether future phone-based text communications should be permitted, determining the likelihood that such communications will cause recipients to opt-out, and the like. Third parties, such as phone service carriers and text communication originating entities, may access the management system via an application programming interface (“API”) to submit data regarding recipient actions, initiate analysis of a potential text communication using the model, and the like.