Cellular Origination Label Monitoring and Correction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Improper or incorrect call labeling by carriers or third-party services can lead to business calls being misidentified as spam, resulting in missed connections and unknown issues for businesses attempting to contact clients or customers, as the original dialer is unaware of the improperly labeled originating call number.
Innovation Solution
A system and method for cellular origination label identification and reporting, which involves a custom dialer application on registered mobile devices to monitor and report call origination labels, allowing users to correct or remove improper labels, enabling efficient management of telephone calls and proactive monitoring of call numbers across multiple cellular networks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If carriers or third-party services perform automated call labeling, then call spam identification is improved, but legitimate business calls are incorrectly labeled as spam causing missed connections
Solution Approach 1:
The system implements a feedback mechanism where call label data is collected from multiple sources including carrier labels, STIR/SHAKEN verdicts, and caller ID names. This feedback loop allows the system to aggregate and analyze labeling information from different carriers and services to determine the most accurate label for each originating call number, thereby reducing false positives while maintaining spam identification effectiveness
Solution Approach 2:
The system serves multiple functions simultaneously: it monitors call labels across different carriers, aggregates labeling data from multiple sources, provides reporting to users, and enables corrective actions. This multi-functional approach allows the system to address various aspects of call labeling accuracy and reliability in a unified platform
2Productivity
If call labels are applied before calls arrive on mobile devices, then spam filtering efficiency is improved, but legitimate business callers are blocked without their knowledge
Solution Approach 1:
The system performs preliminary monitoring and analysis of call labels before calls are filtered by mobile devices. By collecting and aggregating label data from multiple carriers and services in advance, the system establishes a more accurate baseline label that can prevent false positives while maintaining the efficiency of pre-arrival spam filtering
Solution Approach 2:
The system acts as an intermediary between carrier labeling services and mobile device spam filters. It aggregates labeling information from multiple carriers and provides a consolidated, more accurate label that mediates between conflicting carrier assessments, thereby improving the overall accuracy of pre-arrival spam filtering while reducing false positives
3Object-affected harmful factors
If multiple carriers and third-party services independently label calls, then comprehensive spam detection is improved, but labeling consistency and accuracy deteriorate
Solution Approach 1:
The system merges call label data from multiple carriers and third-party services into a unified labeling result. By combining labeling information from diverse sources and applying aggregation logic, the system produces a consistent and accurate label that reflects the consensus or most reliable assessment across multiple services, thereby improving labeling stability while maintaining comprehensive spam detection
Data Source
AI summary
A system and method for automatically determining when a phone number has been improperly negatively labelled, such as spam, by a carrier or third-party labelling service. The system and method use a pool of registered cellular devices to monitor a user provided originating call number, specifically monitoring the originating call number label being attributed to the originating call number by a plurality of carriers represented in the pool of registered mobile devices. After checking the labeling status of a phone number, the system can automatically take corrective action by either correcting the user's number's incorrect label or pulling the user's number from active use.