Rich Object Auto-Suggestion for Input Text
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Solution Overview
Problem
Conventional auto-suggesting methods provide limited and insufficient information, mainly in the form of text, failing to offer rich supplementary content that enhances user experience during input processes such as text input.
Innovation Solution
A computing device provides a trigger indication for suggesting rich objects based on an input sentence, offering supplementary information upon selection, which can include text, images, audio, or hyperlinks, to enrich the input and improve user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional text-based auto-suggestions are used, then the system is simple and easy to implement, but the information provided is not rich enough and user experience is limited
Solution Approach 1:
The patent combines multiple types of content (text, images, audio, video, hyperlinks) into a unified rich object suggestion system. The suggestion module integrates diverse data sources and formats to provide comprehensive auto-suggestions that go beyond traditional text-only responses, thereby increasing content richness while managing system complexity through integrated architecture.
Solution Approach 2:
The suggestion system is designed to handle multiple content types and formats universally. The same suggestion mechanism can provide text completions, image recommendations, audio clips, video segments, and hyperlink suggestions based on user input context, making the system multi-functional and adaptable to different information needs without requiring separate specialized systems for each content type.
2Adaptability or versatility
If rich multi-type suggestions are provided, then user experience is enhanced and information is enriched, but the system complexity increases
Solution Approach 1:
The system dynamically adjusts the type and format of suggestions based on input parameters such as user context, data availability, and interaction history. The suggestion module can change the nature of responses from text-only to multi-media based on detected user preferences and input characteristics, enabling versatile adaptation while managing processing complexity through parameter-driven decision making.
3Productivity
If manual typing is required for all content, then input precision is maintained, but input efficiency is reduced
Solution Approach 1:
The system incorporates feedback mechanisms where suggested rich objects are presented to the user for selection or modification. Users can accept suggestions as-is, modify them, or reject them in favor of custom input. This feedback loop maintains input accuracy by allowing user verification while improving efficiency through automated suggestion generation that reduces the need for complete manual typing.
Data Source
AI summary
According to implementations of the subject matter described herein, a solution is proposed for auto-suggesting. In this solution, a trigger indication for suggesting is provided based on an input sentence. In response to the trigger indication being confirmed, a suggestion for the sentence is provided and the suggestion comprises one or more rich objects. In response to a selection of the suggestion, supplementary information for supplementing the sentence is provided based on at least one selected rich object. In this way, various auto-suggestions comprising rich objects may be provided, and thus rich supplementary information may be provided to supplement the input sentence to enhance the user experience.