Intelligent Keyboard Context-Aware Phrase Suggestions
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Solution Overview
Problem
Current computing devices do not suggest entire phrases to start conversations based on the category of conversation and intent of the user, despite offering word suggestions and auto-correction features.
Innovation Solution
An intelligent keyboard system that provides conversation suggestions by utilizing user-generated content, usage history, profile data, and artificial intelligence to rank and tag content for relevance and context, allowing users to select phrases appropriate for specific conversation types and contexts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If word suggestions and auto-correction are provided, then typing efficiency is improved, but the ability to suggest entire conversation-starting phrases is lost
Solution Approach 1:
The patent combines traditional word suggestion technology with conversation analysis and categorization systems to create a unified keyboard that can suggest both individual words and entire conversation-starting phrases based on contextual understanding
Solution Approach 2:
The system pre-categorizes and pre-organizes conversation phrases by topic, intent, and context before the user needs them, allowing rapid retrieval and suggestion of appropriate phrases without requiring the user to think about what to say next
2Ease of manufacture
If generic word suggestions are provided, then the system is simple to implement, but contextually relevant phrase suggestions cannot be provided
Solution Approach 1:
The system applies different levels of processing and personalization to different aspects of keyboard functionality, maintaining simple word prediction while adding sophisticated contextual analysis specifically for conversation phrase suggestions
Solution Approach 2:
The system continuously learns from user interactions, analyzing which phrases are selected and how they are used to improve future suggestions, creating a feedback loop that enhances contextual relevance without requiring complete system redesign
3Measurement precision
If comprehensive user data is collected for personalization, then conversation suggestion accuracy is improved, but system complexity increases
Solution Approach 1:
The system divides user data into distinct categories (typing patterns, conversation topics, personal preferences, usage timing) and processes each segment separately through specialized algorithms, making the overall complex system more manageable and efficient
Data Source
AI summary
An intelligent keyboard for mobile devices and other computer devices. This intelligent keyboard provides the user with suggestions of relevant words or phrases that can be used to start or continue a conversation on text message, email and/or various web applications. The intelligent keyboard provides conversation suggestions that are appropriate for given application contexts, categories, and conversation types. The intelligent keyboard uses user generated content from application users, usage history, profile data, dialogue data, platform generated content from the system managers/owners, content collected from various websites/integrations and natural language content generated by artificial intelligence. Content is ranked by preference, contextual suitability, and performance. Content is further tagged for application context. User behavior, user data and artificial intelligence models continuously update the system so that the relevance and performance of keyboard content is optimized.