Context-Aware Suggestion Manager for Proactive Data Entry
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Solution Overview
Problem
Existing autocomplete systems typically display suggestions only after the user has entered characters or upon immediate selection, failing to provide relevant suggestions before content entry or during pauses, and often limit suggestions to visible data within the document.
Innovation Solution
Implementing a suggestion manager that automatically displays relevant suggestions before content entry, based on user selection or detected pauses, including both visible and hidden data from within and outside the document, using a system that integrates with touch input devices and can filter suggestions dynamically as the user types.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If suggestions are displayed only after user enters characters, then the system avoids displaying irrelevant suggestions, but users must type more characters to get relevant suggestions
Solution Approach 1:
The system performs preliminary action by displaying suggestions before the user enters any characters. The suggestion manager proactively retrieves and displays context-aware suggestions based on the selected content area, allowing users to select from pre-displayed options without typing, thus reducing time loss while maintaining relevance through context-based filtering
2Ease of operation
If suggestions are displayed before content entry, then user experience is enhanced with proactive suggestions, but the system must process more data to generate relevant suggestions
Solution Approach 1:
The system applies local quality by providing context-aware suggestions specific to the selected content area rather than generating general suggestions for the entire document. The suggestion manager analyzes the local context (selected cell, row, or column) and retrieves relevant suggestions from appropriate data sources, reducing unnecessary data processing while enhancing user experience with targeted suggestions
3Device complexity
If suggestions include only visible data, then the system reduces data retrieval complexity, but users cannot access suggestions from hidden or external data sources
Solution Approach 1:
The system implements universality by enabling the suggestion manager to retrieve suggestions from multiple data sources including visible data, hidden data within the document, and external data sources. The system automatically determines which data sources to query based on the selected content area and suggestion type, providing comprehensive coverage while managing complexity through automated source selection and filtering
Data Source
AI summary
Suggestions are automatically displayed in response to an event. For example, suggestions may be automatically displayed in response to a receiving an indication from a user to enter content (e.g. receiving a selection of a content entry area). The suggestions may be displayed before a user enters any characters and before an input device is displayed and/or used (e.g. keyboard, Software Input Panel (SIP), and the like. Suggestions may also be automatically displayed in response to detecting a pause while a user is entering content. For example, when a user is actively entering content, suggestions are not automatically displayed but when a user pauses a predetermined amount while entering content, suggestions are automatically displayed. The suggestions may be determined from content that may be seen on a display and/or hidden from view (e.g. hidden rows in a spreadsheet).