Context-Based CNAM Assignment for Credible Incoming Call Identification
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Solution Overview
Problem
Mobile device users face challenges in identifying the credibility of incoming calls, particularly from unknown or unfamiliar numbers, with limited tools to distinguish between reputable and spam or scam callers, leading to a high rate of unanswered business calls.
Innovation Solution
A system and method that utilizes a call content application programming interface (API) to access and assign a first or second caller identification name (CNAM) based on the context of the calling device number, allowing for the selection and assignment of appropriate CNAMs to enhance caller identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional caller identification is used, then the system is simple, but users cannot reliably identify the credibility of incoming calls
Solution Approach 1:
The patent introduces a content delivery device as an intermediary between the calling device and the mobile device. This intermediary delivers context-based CNAM data to the mobile device, enabling reliable call credibility identification without requiring the calling device to directly provide verification information. The intermediary handles the complexity of data delivery and context matching.
Solution Approach 2:
The system performs preliminary actions by determining context information about the calling device and assigning appropriate CNAM data before the call reaches the mobile device. This preliminary context determination and CNAM assignment happens in advance, allowing the mobile device to display credible identification information immediately when the call arrives.
2Measurement precision
If multiple CNAMs are provided for a single calling device number, then call identification accuracy improves, but the system complexity increases
Solution Approach 1:
The patent implements a dynamic CNAM assignment system where the selected CNAM changes based on real-time context information about the calling device. Instead of a static one-to-one mapping, the system dynamically determines which CNAM to assign based on current call context, enabling accurate identification while managing complexity through automated context-based selection.
Solution Approach 2:
The system changes the parameter of CNAM assignment based on context information parameters. By determining context about the calling device and using that context to select between multiple CNAMs, the system adapts the identification information to match the actual calling scenario, improving accuracy without requiring manual intervention.
3Reliability
If real-time CNAM assignment based on context is implemented, then call response accuracy improves, but processing time increases
Solution Approach 1:
The system performs context determination and CNAM selection in advance, before the call reaches the mobile device. By completing these actions preliminarily at the content delivery device, the actual call processing at the mobile device remains fast and simple, minimizing time loss while maintaining high response accuracy.
Data Source
AI summary
One example method of operation may include identifying a call originated from a caller entity destined for a called entity at a call content server, identifying a called number associated with the called entity and a caller number associated with the caller entity, comparing a telephone number prefix associated with the called number with a number of enhanced call content data elements to identify a match, selecting one or more of the enhanced call content data elements to pair with the called number based on the match, and forwarding the selected enhanced call content data elements to the called entity.