Document Suggestion System Throttling via Typing Speed Analysis
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Solution Overview
Problem
Document editing applications lack effective tools to provide users with contextually relevant suggestions during the editing process, leading to inefficiencies and missed opportunities for assisting users with information inclusion.
Innovation Solution
A suggestion system that uses historical performance measures from user sessions to train a model for predicting when and how to provide textual suggestions, throttling suggestions based on user typing speed, device latency, and suggestion acceptance rates to enhance relevance and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If suggestions are provided continuously during document editing, then the completeness of assistance is improved, but the user experience deteriorates due to excessive interruptions and reduced typing flow
Solution Approach 1:
The system dynamically adjusts the suggestion provision strategy based on real-time detection of user typing patterns. When rapid typing is detected, the system suppresses suggestions to maintain flow; when slower typing is detected, the system provides suggestions to enhance assistance. This dynamic adaptation resolves the contradiction between providing complete assistance and maintaining user experience.
Solution Approach 2:
The system changes the parameter of suggestion frequency based on detected typing speed. By monitoring typing patterns and adjusting the suggestion provision rate accordingly, the system optimizes the balance between assistance completeness and user experience, providing suggestions only when they are likely to be helpful rather than intrusive.
2Productivity
If suggestions are provided at high frequency, then the assistance coverage is improved, but the relevance of suggestions deteriorates due to interruptions in user thought flow
Solution Approach 1:
The system dynamically adjusts suggestion frequency based on detected typing patterns. When rapid typing is detected, the system suppresses suggestions to maintain flow; when slower typing is detected, the system provides suggestions to enhance assistance. This dynamic adaptation resolves the contradiction between providing complete assistance and maintaining user experience.
Solution Approach 2:
The system uses feedback from detected typing patterns to adjust suggestion provision. By monitoring typing speed and patterns, the system receives feedback about user engagement and adjusts the suggestion frequency accordingly, improving relevance by providing suggestions only when the user is likely to be receptive.
3Adaptability or versatility
If a suggestion system is implemented without throttling, then the assistance availability is improved, but the system complexity increases due to need for performance monitoring and adaptive control
Solution Approach 1:
The system monitors its own performance metrics (typing speed, suggestion acceptance rates, latency) and uses this self-generated data to automatically adjust suggestion provision. This self-service approach allows the system to adapt to user needs without requiring complex external control mechanisms, thereby improving assistance availability while limiting the increase in system complexity.
Solution Approach 2:
The system uses feedback from detected typing patterns and suggestion acceptance rates to adjust suggestion provision. By monitoring typing speed and patterns, the system receives feedback about user engagement and adjusts the suggestion frequency accordingly, improving relevance by providing suggestions only when the user is likely to be receptive.
4Stability of the object's composition
If suggestions are provided without considering user typing speed, then the assistance consistency is improved, but the usefulness of suggestions deteriorates due to mismatch with user workflow
Solution Approach 1:
The system dynamically adjusts suggestion frequency based on detected typing patterns. When rapid typing is detected, the system suppresses suggestions to maintain flow; when slower typing is detected, the system provides suggestions to enhance assistance. This dynamic adaptation resolves the contradiction between providing complete assistance and maintaining user experience.
Solution Approach 2:
The system changes the parameter of suggestion frequency based on detected typing speed. By monitoring typing patterns and adjusting the suggestion provision rate accordingly, the system optimizes the balance between assistance completeness and user experience, providing suggestions only when they are likely to be helpful rather than intrusive.
Data Source
AI summary
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing suggestions within a document. In one aspect, a method includes obtaining textual input provided to a document editing application by a user device, the textual input being provided to the document editing application for inclusion in a document; identifying performance measures associated with the current editing session for the document, each performance measure being based on session data obtained from the user device during a document editing session, the session data being for the textual input and prior text that was included in the document prior to the textual input; providing the performance measures as input to a suggestion model that was trained using historical performance measures identified in performance logs for historical document editing sessions of users; and throttling textual suggestions during the current editing session based on the output of the suggestion model.