Address Book Search Tool for Automatic Contact Updates
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Solution Overview
Problem
Users often face incomplete or inaccurate contact information in their address books, with information not being updated in a timely manner, leading to potential mistakes or missing details.
Innovation Solution
A method and apparatus for providing a search tool that automatically updates contact information in response to specific events, allowing users to select or automatically adopt new information based on search results, and integrates with address book management services for continuous updates and notifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual address book updates are used, then user control over contact information is maintained, but information accuracy and completeness deteriorate over time
Solution Approach 1:
The system performs preliminary actions by automatically searching for and retrieving contact information updates before the user needs them. When a contact entry is added or viewed, the system proactively queries external databases and services to obtain current information, preparing updated data in advance so it is ready when the user needs it, eliminating the need for manual update timing decisions.
Solution Approach 2:
The address book system performs self-service by automatically maintaining contact information without requiring user intervention. The system autonomously searches external sources, retrieves updated contact details, and manages the update process itself, freeing the user from the burden of manually tracking and updating contact information while maintaining high accuracy.
2Loss of information
If comprehensive search is performed for contact updates, then information completeness is improved, but resource consumption increases
Solution Approach 1:
The system applies local quality by adjusting search intensity and scope based on specific conditions and contexts. Different search strategies are employed depending on the contact type, available data quality, user preferences, and device state. For example, high-priority contacts may receive comprehensive searches while less critical contacts use lighter verification, optimizing resource allocation to match the actual information needs of each contact entry.
Solution Approach 2:
The system implements partial action by performing searches at different levels of thoroughness based on needs. Rather than always executing exhaustive searches, the system selectively applies comprehensive searches only when necessary to achieve information completeness, using lighter verification methods for routine updates, thus avoiding excessive resource consumption while maintaining adequate information quality.
3Reliability
If automatic search is always performed, then contact information currency is improved, but device complexity increases
Solution Approach 1:
The system exhibits dynamics by making the search automation behavior adaptive and configurable rather than static and fixed. Users can adjust search frequency, trigger conditions, and automation levels according to their preferences and needs. The system dynamically adjusts its behavior based on contextual factors such as contact importance, available resources, and user interactions, allowing flexibility in managing automatic search operations.
Solution Approach 2:
The system achieves universality by designing a multi-functional search automation framework that handles various contact update scenarios through a unified mechanism. The same core search infrastructure serves multiple purposes: initial contact creation, periodic updates, event-triggered searches, and user-initiated queries. This multi-functional approach reduces overall system complexity compared to implementing separate dedicated systems for each update scenario.
4Measurement precision
If user review of search results is required, then information accuracy is improved, but ease of operation deteriorates
Solution Approach 1:
The system applies partial action by requiring user review only when necessary rather than for all updates. High-confidence matches from reliable sources can be automatically accepted without user intervention, while uncertain or conflicting results are presented for review. This selective approach maintains high accuracy for critical updates while preserving ease of operation for routine corrections, avoiding the need for universal user review.
Solution Approach 2:
The system implements feedback mechanisms that learn from user review patterns to improve automation over time. When users review and accept or reject search results, the system uses this feedback to refine its matching algorithms, source reliability assessments, and automatic acceptance criteria. This feedback loop gradually reduces the number of cases requiring manual review while maintaining or improving accuracy, thereby enhancing ease of operation without sacrificing verification quality.
Data Source
AI summary
A method for providing a search tool for use in connection with address book management may include receiving an indication of an address book update event associated with a contact of an address book of a user, causing performance, via a processor, of a search responsive to receipt of the indication, and enabling modification of contact information associated with the contact based on the search results. A corresponding apparatus and computer program product are also provided.