Context-Aware Message Suggestions for Mobile Typing
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional electronic messaging systems fail to provide context-specific suggestions, as they rely on pre-generated generic messages that do not account for the user's current activity or external context, such as location and calendar information, leading to inadequate responses when the user is engaged in activities that make typing difficult, like walking or running.
Innovation Solution
A computer-implemented method that detects the initiation of composing an electronic message, obtains contextual information from external sources like user location, calendar, and previous messages, and provides more detailed suggestions based on measured gravitational force and user activity, such as walking or running, to offer context-specific responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If pre-generated generic messages are used for suggestions, then the system complexity is reduced and operation is simplified, but the message relevance and context-specificity deteriorate
Solution Approach 1:
The system pre-obtains contextual information from external sources (calendar, location, contacts) before the user needs to compose a message. This preliminary gathering of context enables the suggestion system to provide relevant, context-specific messages without requiring complex real-time analysis when the user is actively typing, thus maintaining ease of operation while improving message relevance.
Solution Approach 2:
The patent introduces an intermediary layer between the user and the message suggestions - a context analysis module that processes external contextual information (calendar events, location data, contact information) and translates it into relevant message suggestions. This intermediary handles the complexity of context interpretation while presenting simplified, relevant options to the user.
2Loss of information
If context-specific suggestions are provided, then message relevance is improved, but the device complexity and processing requirements increase
Solution Approach 1:
The suggestion system is segmented into multiple independent modules: a context information obtainer that gathers data from external sources, a context analyzer that processes this information, and a suggestion generator that creates relevant messages. This segmentation allows each module to handle specific tasks independently, reducing overall system complexity while enabling context-specific suggestions.
Solution Approach 2:
The system automatically obtains and processes contextual information from external sources without requiring user input or manual configuration. The context analysis and message generation happen autonomously based on available device data (calendar, location, contacts), reducing the complexity of user interaction while providing personalized suggestions.
3Reliability
If detailed suggestions are provided during user activities like walking or running, then message helpfulness is improved, but the processing time and computational resources increase
Solution Approach 1:
The system detects user activities (walking, running, driving) in advance and pre-prepares context-specific suggestions based on detected patterns. By identifying activity states early and having relevant suggestions ready beforehand, the system minimizes processing delays while providing timely, helpful message suggestions during transient activities.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution provides more accurate and relevant message suggestions that account for the user's activity and context, enhancing the messaging experience by offering fully formed sentences instead of generic words, improving user engagement and message relevance.
Implementation Method 1
the detecting of the operating condition is based on a measured gravitational force
Data Source
AI summary
A computer-implemented technique can include detecting an initiation of composing an electronic message by a user, obtaining contextual information for the electronic message from a source external to a text of the electronic message, obtaining a first suggestion for the text of the electronic message based on the contextual information, detecting an operating condition indicative of a user activity during which the user is likely to experience difficulty in typing, in response to detecting the operating condition, obtaining a second suggestion for the electronic message based on the contextual information, the second suggestion being more detailed than the first suggestion, and outputting one of the first and second suggestions depending on one or more other conditions.