Assistant Application Widgets Tuned to User Familiarity
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Solution Overview
Problem
Existing automated assistants often provide duplicative content when interacting with other applications, wasting resources and interrupting current processes due to overlapping functionality, and fail to consider the user's familiarity with the subject matter.
Innovation Solution
An automated assistant that generates relevant application widgets based on user familiarity, determined through contextual data and machine learning models, to provide tailored responses without duplicating application content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the automated assistant processes user requests independently without considering other applications, then it can provide responsive service, but it generates duplicative content and wastes computational resources
Solution Approach 1:
The patent merges the automated assistant's content generation with the application's existing content by detecting when the assistant's response would duplicate application content and suppressing or modifying such duplicative output. This combines the responsiveness of the assistant with the resource efficiency of avoiding redundant processing.
Solution Approach 2:
The system implements feedback by having the automated assistant detect application content that is already being rendered, use this information to determine whether to generate duplicative content, and adjust its response accordingly. This feedback loop prevents resource waste while maintaining user responsiveness.
2Adaptability or versatility
If the automated assistant provides generic responses without considering user familiarity, then it can serve all users uniformly, but it fails to provide personalized and relevant information
Solution Approach 1:
The system performs preliminary actions by assessing user familiarity with the subject matter before generating the assistant response. This advance assessment allows the system to tailor the response appropriately without adding significant complexity during the main response generation process.
Solution Approach 2:
The patent applies local quality by providing different types of information based on the specific user's familiarity level with the subject matter. Rather than a uniform approach, the system adjusts the content quality and detail locally for each user based on their demonstrated knowledge level.
3Reliability
If the automated assistant renders detailed content for unfamiliar users, then it can ensure comprehensiveness, but it increases information overload for users who already know the subject
Solution Approach 1:
The system applies dynamics by adjusting the amount and type of information provided based on the user's familiarity level. For unfamiliar users, it provides comprehensive detailed information; for familiar users, it provides concise summaries or supplements. This dynamic adaptation prevents information overload while maintaining completeness where needed.
Data Source
AI summary
Implementations set forth herein relate to an automated assistant that can provide interactive application widgets based on their relevance to content that a user may have expressed interest in. The automated assistant can render the application widgets according to an estimated familiarity of the user with the content they expressed interest in. Each application widget can correspond to an application that can be accessed separately from the automated assistant. An application widget can be rendered at a display interface simultaneous to the user accessing the content that served as the basis for rendering the application widget. When the user interacts with the application widget, the automated assistant can communicate selection data to a corresponding application, which can respond with supplemental data that can be rendered at the display interface.