Interactive Recommendation Prompts for Low-Interference User Operations
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Solution Overview
Problem
Traditional human-computer interactive processes are often passive, with smart devices responding only to user-initiated operations, leading to potential interference when content recommendations are initiated, disrupting the user's current activity.
Innovation Solution
A method and system for determining a prompt mode based on user and environmental characteristics to minimize interference by using various prompt modes such as system, user interface, vibration, and voice prompts for content recommendations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If content recommendation is initiated to a user, then the user may receive useful information, but it may cause interference to the user's current operation
Solution Approach 1:
The patent applies local quality by differentiating the prompt mode based on the specific characteristics of the recommended content and user context. Different types of recommendations (e.g., news, weather, messages) are delivered through different prompt modes (system prompt, user interface prompt, vibration prompt, voice prompt), allowing each recommendation to be delivered in the most appropriate manner for its specific nature, thereby reducing unnecessary interference while ensuring useful information is conveyed.
Solution Approach 2:
The patent implements dynamics by making the prompt mode adaptive and changeable based on real-time conditions. The system dynamically selects from multiple prompt modes (system prompt, user interface prompt, vibration prompt, voice prompt) according to user characteristics, environmental factors, and content type. This dynamic adaptation allows the recommendation system to respond flexibly to changing user states and contexts, minimizing interference when the user is engaged in important tasks while maximizing information delivery when appropriate.
2Loss of information
If multiple prompt modes are used for content recommendation, then the information can be delivered more effectively, but the system complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-defining multiple prompt modes (system prompt mode, user interface prompt mode, vibration prompt mode, voice prompt mode) and their corresponding conditions before actual recommendation delivery. The system establishes a framework in advance that maps different recommendation scenarios to appropriate prompt modes, so that when a recommendation needs to be delivered, the system can quickly select from pre-established options rather than creating new solutions in real-time, thereby reducing the operational complexity despite having multiple modes.
Solution Approach 2:
The patent implements universality by creating a unified recommendation system that can handle multiple types of recommendations through a common multi-mode prompt framework. The same system architecture and selection logic are used across different recommendation types (news, weather, messages, etc.), allowing the system to serve multiple functions through a single multi-capable structure. This universal approach reduces overall system complexity compared to having separate systems for each recommendation type.
Data Source
AI summary
The present disclosure example discloses a method for displaying an interactive interface of a recommended behavior. The method may include determining a prompt mode according to at least one of recommended content associated with a first user, one or more user characteristics associated with the first user, one or more environmental characteristics of a user terminal associated with the first user, or one or more first presentation data characteristics associated with the user terminal, the prompt mode including at least one of a plurality of system prompt modes of the user terminal, a plurality of user interface prompt modes of the user terminal, a vibration prompt mode of the user terminal, or a voice prompt mode of the user terminal; and prompting the first user for the recommended content based on the prompt mode.