Address Input Assistance via Profile Relevancy Scoring
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Solution Overview
Problem
Existing communication systems, such as email and instant messaging, require users to manually input recipient addresses, which can be time-consuming and prone to errors, especially when dealing with multiple contact information types like email addresses, phone numbers, and IM usernames, and do not provide real-time suggestions based on user behavior and profile data.
Innovation Solution
A computer-implemented method and system that scans user messages to identify addresses, generates profiles for individuals, computes relevancy scores, and provides real-time suggestions for completing incomplete address inputs by matching user input with profile data, including names, email addresses, phone numbers, and social media information, allowing users to select and insert the most relevant addresses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If users manually input recipient addresses in communication systems, then the system can accurately identify recipients, but the process becomes time-consuming and prone to errors
Solution Approach 1:
The system performs preliminary actions by scanning user messages and generating profiles with addresses in advance, before the user needs to input an address. This pre-computation of contact information allows rapid retrieval and suggestion during actual communication, eliminating the need for manual typing while ensuring accuracy through pre-validated profiles
Solution Approach 2:
The system serves itself by automatically scanning messages, extracting addresses, generating profiles, and computing relevancy scores without user intervention. This self-service mechanism populates the address suggestions automatically, allowing the system to maintain accurate recipient identification while minimizing the time users spend on address input
2Productivity
If the system provides real-time address suggestions based on user behavior and profile data, then user efficiency improves, but the system complexity increases
Solution Approach 1:
The system merges multiple functions into a unified profile management mechanism: scanning messages, extracting addresses, storing profiles, computing relevancy scores, and providing suggestions all occur within a single integrated system. This consolidation reduces overall system complexity compared to having separate systems for each function, while still delivering real-time suggestions that improve user efficiency
Solution Approach 2:
The profile system serves multiple purposes: it stores contact information for future use, analyzes user behavior patterns, computes relevancy scores for suggestions, and provides real-time assistance during address input. This multi-functionality allows the same infrastructure to support both improved productivity and controlled complexity by reusing the same data structures and processing mechanisms across different operations
3Measurement precision
If the system scans and processes user messages to generate profiles, then accurate suggestions can be provided, but the processing time and computational resources increase
Solution Approach 1:
The system performs message scanning and profile generation as preliminary actions in the background, before the user needs to input an address. By pre-processing messages and extracting addresses ahead of time, the system maintains high measurement precision for suggestions while minimizing the perceived processing time for users, as the heavy computational work occurs beforehand
Solution Approach 2:
The system employs periodic action by scanning and processing messages at intervals rather than continuously, updating profiles periodically based on new messages. This approach maintains accurate suggestion data while reducing computational overhead and processing time compared to continuous real-time analysis, balancing precision with resource efficiency
Data Source
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AI summary
Systems and methods to provide assistance for completion during address input. In one aspect, a method includes automatically generating profiles for persons identified in messages, such as incoming and outgoing emails. Based on how the addresses of the persons are used in incoming and outgoing messages, the relevancy scores of the addresses are determined. When a user is typing an address, the profiles and the relevancy scores are used to identify and sort suggestions for the completion of the address input.