Communication Profile Generation for Personalized Initiation
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Solution Overview
Problem
Autofill and autocomplete systems in electronic communication fail to suggest how to initiate communications and do not account for the recipient's likely response, nor are they customized to the user's voice or expertise.
Innovation Solution
A system that generates user communication profiles based on electronic transcripts, including topical expertise, language fluency, avoided topics, and preferred topics, to provide personalized communication initiation recommendations by identifying suitable conversation partners and suggesting opening lines tailored to both users' communication styles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If basic autocomplete suggestions are provided based on previous communications, then users receive automated reply suggestions, but the suggestions are not customized to the user's voice or expertise and fail to capture user personality
Solution Approach 1:
The system performs preliminary analysis of user communications to generate communication profiles before actual communication needs arise. By pre-processing communication history and extracting user preferences, expertise areas, and communication patterns, the system prepares personalized data structures that enable customized autocomplete suggestions without adding complexity during real-time usage
Solution Approach 2:
The system uses the user's own communication history as training data to automatically generate personalized profiles. By analyzing the user's past communications, the system self-adapts to capture the user's voice, expertise, and communication style without requiring manual configuration or external intervention
2Reliability
If autocomplete suggestions are generated from previous communications, then users receive automated reply ideas, but the suggestions fail to account for how the recipient is likely to respond
Solution Approach 1:
The system incorporates recipient communication patterns and response tendencies into the autocomplete suggestion generation process. By analyzing how recipients typically respond to different types of messages and using this feedback to adjust suggestions, the system improves response effectiveness while leveraging existing communication data
Solution Approach 2:
The system pre-analyzes recipient communication patterns and response tendencies before generating suggestions. By preparing recipient profile data and response probability models in advance, the system can quickly evaluate suggested messages against recipient preferences without adding real-time computational complexity
3Adaptability or versatility
If communication profiles are generated for multiple users based on electronic transcripts, then personalized communication initiation recommendations can be provided, but the system complexity and data processing requirements increase
Solution Approach 1:
The system uses a universal communication profile data structure that serves multiple functions: capturing user expertise, communication style, preferences, and response patterns. This multi-functional profile framework enables various personalized features (autocomplete, communication initiation recommendations, partner matching) without requiring separate complex systems for each function
Solution Approach 2:
The system dynamically adjusts profile parameters and weighting based on the specific communication context and user needs. By changing which profile attributes are most relevant in different situations (e.g., emphasizing expertise in technical communications vs. casual conversations), the system provides personalized recommendations without maintaining excessive complexity in all profile aspects simultaneously
Data Source
AI summary
Systems, methods, and computer-readable storage media for providing communication recommendations to users. The system receives electronic transcripts associated with a first user and generates, based on the transcripts, a communication profile of the user. The system also receives additional user transcripts associated with a plurality of additional users and generates additional communication profiles for those additional users based on the additional transcripts. The system receives a request to communicate with at least one user within the plurality of additional users regarding a specified topic, identifies a second user from within the plurality of additional users, and generates a communication initiation recommendation for the first user to communicate with the second user. The system then transmits the communication initiation recommendation to a first user computing device associated with the first user.