Group-Based Call Handling Using User Vote Thresholds
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Solution Overview
Problem
Current call handling systems lack the ability to effectively manage calls from undesirable sources based on user associations with groups, leading to inconsistent and inefficient handling of calls from telemarketers and other unwanted callers.
Innovation Solution
A call handling system that allows users to cast votes on call sources and apply these votes to user groups, determining how to handle incoming calls based on the number of votes, including options to block, forward, or present calls differently depending on vote thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If calls from undesirable sources are blocked at the national level (e.g., National Do Not Call Registry), then call recipients are protected from unwanted calls, but individual users lose control over their personal call preferences and cannot customize blocking based on their specific associations with call sources
Solution Approach 1:
The system applies different call handling treatments to different users based on their individual associations with call sources. Each user can have personalized blocking decisions based on their specific interactions and preferences, rather than applying a uniform national registry approach. The system determines treatment based on the specific user's association history and preferences with particular call sources.
Solution Approach 2:
The system segments the call handling decision-making process into individual user-specific associations rather than a centralized national registry. Each user maintains their own association data and blocking decisions, allowing granular control over which call sources are blocked for which users based on individual experiences and preferences.
2Ease of operation
If individual recipients manually specify call sources to block, then users maintain control over their preferences, but the system becomes complex and requires significant user input and maintenance
Solution Approach 1:
The system automatically determines user associations with call sources by analyzing actual call interactions and user behaviors. Rather than requiring users to manually input blocking preferences, the system self-determines associations through observed call patterns, user responses, and interaction history, reducing the burden on users while maintaining personalized control.
Solution Approach 2:
The system continuously learns from user interactions with calls and adjusts associations accordingly. User feedback from call responses, blocking actions, and interaction patterns is used to refine and update user associations with call sources automatically, reducing the need for manual specification while maintaining accurate personalized preferences.
3Adaptability or versatility
If the system tracks and stores user associations with call sources, then personalized call handling is enabled, but data storage requirements and system processing complexity increase
Solution Approach 1:
The system stores and processes only the necessary association data required for determining call treatment, rather than maintaining comprehensive detailed records of all call interactions. The system selectively stores user association information that is directly relevant to blocking decisions, minimizing data storage requirements while enabling personalized handling.
Solution Approach 2:
The system manages association data through simplified data structures and parameters that capture essential user-call source relationships without storing unnecessary detailed information. The association data is structured to store only the critical information needed for determining treatment, such as user identifiers, call source identifiers, and association strength, rather than complete interaction histories.
4Reliability
If the system applies call blocking based on national registry listings, then widespread protection is achieved, but the system cannot respond to emerging call sources or adapt to changing user preferences in real-time
Solution Approach 1:
The system proactively determines and applies blocking decisions based on user associations before calls occur. By pre-determining which call sources should be blocked for which users based on historical associations and patterns, the system can prevent unwanted calls without requiring real-time manual intervention or waiting for national registry updates.
Solution Approach 2:
The system continuously monitors call interactions and user responses to learn and adapt to emerging call sources and changing preferences in real-time. This feedback mechanism allows the system to automatically update user associations and blocking decisions based on current user behavior patterns, enabling rapid adaptation to new telemarketing tactics and user preferences without waiting for centralized registry updates.
Data Source
AI summary
A method is described for call treatment based on user association with one or more user groups. The method includes receiving a phone call from a call source that is directed to a call recipient, identifying a user group associated with the call recipient, and determining a number of received indications assigned to the user group. The received indications are assigned to the user group by users associated with the user group, and the received indications reflect a desire by the users for a special treatment of future calls from the call source. The method also includes distinguishing treatment of the phone call from the call source based on the number of received indications.