Predicted Contact List Generation for Caller ID
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Solution Overview
Problem
In a BYOD or enterprise-issued device environment, users often miss important calls from contacts not stored on their device, leading to declined calls due to unknown numbers, as the phone application cannot display caller information for non-local contacts, resulting in missed interactions within or outside the enterprise.
Innovation Solution
Generating a list of predicted contacts based on user interactions, organizational hierarchy, role, seasonal interactions, and location-specific contacts, which are synchronized with the device to provide caller information for incoming calls, even if the contact is not locally stored.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all enterprise contacts are stored on the mobile device, then caller information can be displayed for all contacts, but device storage is consumed excessively
Solution Approach 1:
The contact database is segmented into local contacts stored on the device and remote contacts stored in the enterprise directory server. The system synchronizes only necessary contact information to the device while maintaining the ability to access additional contacts remotely, thus reducing device storage consumption while preserving caller information availability.
Solution Approach 2:
A synchronization service acts as an intermediary between the device contact database and the enterprise directory server. This mediator manages which contacts are synchronized to the device based on usage patterns and importance, allowing the system to balance between having contacts locally available and minimizing device storage usage.
2Quantity of substance
If contacts are not stored locally on the device, then device storage is conserved, but caller information cannot be displayed for incoming calls from unknown numbers
Solution Approach 1:
The system performs preliminary synchronization of frequently contacted enterprise directory contacts to the device before they are needed for call identification. By proactively syncing contacts based on interaction history and organizational hierarchy, the system ensures caller information is available when needed while minimizing device storage usage.
Solution Approach 2:
The system uses feedback from call logs and messaging interactions to dynamically adjust which contacts are synchronized to the device. Contacts that are frequently contacted are prioritized for local storage, while less frequently contacted contacts remain on the server, optimizing the balance between storage conservation and caller identification capability.
3Speed
If the global address list is limited to a subset of enterprise contacts, then synchronization speed is improved, but contacts from different locations or groups are missing
Solution Approach 1:
The global address list synchronization is made dynamic rather than static. The system continuously monitors interaction patterns, location data, and organizational changes to dynamically update the synchronized contact list. This allows the system to maintain fast synchronization speeds while progressively expanding contact coverage to include users from different locations and groups as they become relevant.
4Object-affected harmful factors
If users decline calls from unknown numbers, then spam calls are reduced, but important calls from enterprise contacts are missed
Solution Approach 1:
The system provides self-service by automatically identifying and flagging enterprise directory contacts in the global address list. When a call comes from a number not in the local contact database, the system automatically checks the enterprise directory and displays the caller's organizational information, allowing users to make informed decisions about answering without manually researching unknown numbers.
Data Source
AI summary
Disclosed are various embodiments for generating a list of predicted contacts that can be provided to a client device. The predicted contacts can be generated based upon an analysis of user interaction data. The predicted contacts can be made available to a phone application or messaging application on a client device so that contact information can be displayed in response to an incoming call or a message.


