Predictive Response Selection Using User Frequency Data
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Solution Overview
Problem
Computing devices often provide either limited or excessive pre-defined response options for incoming communications, making it difficult for users to select a relevant response without manually entering textual information, which can be inefficient and inconvenient.
Innovation Solution
A computing system determines candidate responses based on their frequency of selection by users for similar communications, sending these relevant responses to the user's device, allowing for quick selection and reducing the need for manual input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a computing device provides a small number of stored responses, then the device complexity is reduced, but the likelihood that the available stored responses include a response desired by the user decreases
Solution Approach 1:
The system pre-generates and stores multiple candidate responses for common communication scenarios before they are needed. When a user receives an incoming communication, the system quickly retrieves pre-prepared response options based on the communication type, sender, and context, eliminating the need for users to manually compose responses from scratch while maintaining a manageable storage size through selective pre-computation.
2Adaptability or versatility
If a computing device provides a larger number of stored responses, then the likelihood that the available stored responses include a response desired by the user increases, but the user requires more time to search through the responses
Solution Approach 1:
The system incorporates feedback mechanisms that track user selections and preferences over time. When users consistently choose certain response types or modify specific responses, the system learns from this feedback and adjusts the candidate response generation to prioritize similar options in the future. This feedback loop enables the system to refine its response suggestions, presenting fewer but more accurate options that align with user preferences.
Solution Approach 2:
The system dynamically adjusts parameters such as the number of candidate responses presented, the specificity of response templates, and the weighting of different response categories based on the communication context, user history, and time of day. For example, during work hours the system may prioritize professional responses, while at other times suggesting more casual options, thereby reducing user search time while maintaining response relevance.
3Manufacturing precision
If users manually input textual information to respond, then the precision and relevance of the response increases, but the productivity decreases
Solution Approach 1:
The system pre-generates multiple candidate responses for common communication scenarios before they are needed. When a user receives an incoming communication, the system quickly retrieves pre-prepared response options based on the communication type, sender, and context, eliminating the need for users to manually compose responses from scratch while maintaining a manageable storage size through selective pre-computation.
Solution Approach 2:
The system creates and maintains a library of template responses that can be copied and adapted for similar communication scenarios. These templates are organized by communication type, sender relationships, and contextual parameters, allowing users to quickly select and slightly modify pre-written responses rather than composing entirely new messages, thereby maintaining response quality while significantly reducing input time.
Data Source
AI summary
A computing system includes at least one processor and at least one module, operable by the at least one processor to receive, from a computing device associated with a user, an indication of an incoming communication, the incoming communication including information and determine, based at least in part on the information included in the incoming communication, one or more candidate responses to the incoming communication, wherein each candidate response includes information to be sent by the computing device to at least one other computing device, and wherein at least one candidate response was previously selected at least at a threshold frequency by at least one of the user and one or more other users. The at least one module is further operable by the at least one processor to send, to the computing device, a set of candidate responses from the one or more candidate responses.