Context-Aware Intelligent Assistant Response Ranking
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Solution Overview
Problem
Intelligent automated assistants often provide predetermined, canned responses that are not contextually appropriate or informative, especially in conversational scenarios where factual answers are not applicable, leading to cumbersome user interactions and inefficiencies.
Innovation Solution
The system analyzes unstructured natural language information to determine contextually appropriate predicted responses based on user-specific and conversational context, selecting from multiple candidate responses to provide relevant and customized suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If predetermined canned responses are provided to users, then the device can respond to all user inputs, but the responses are not contextually appropriate or informative
Solution Approach 1:
The system pre-generates multiple candidate responses with different contextual relevances before user input is processed. These candidate responses are ranked in advance based on their potential contextual appropriateness, allowing the system to quickly select the most relevant response without extensive real-time computation.
Solution Approach 2:
The patent replaces traditional rule-based response selection with a machine learning model that automatically ranks candidate responses based on contextual relevance. This substitution enables the system to understand conversational context and select appropriately tailored responses rather than relying on predetermined rigid response rules.
2Adaptability or versatility
If context analysis is performed to provide customized responses, then response relevance is improved, but computational complexity and processing time increase
Solution Approach 1:
The system performs preliminary analysis by pre-generating multiple candidate responses and pre-computing their contextual relevance scores before the user actually interacts with the system. This advance preparation reduces the computational burden during real-time interaction, as the heavy lifting of context analysis has already been done.
Solution Approach 2:
The patent changes the parameter of response generation from creating one response at a time to generating multiple candidate responses simultaneously with different contextual parameters. This allows the system to explore multiple contextual interpretations in parallel and select the best match, improving both customization and efficiency.
3Reliability
If multiple candidate responses are generated and ranked, then response quality is improved, but the time and energy required for processing increases
Solution Approach 1:
The system generates and ranks multiple candidate responses in advance, before they are needed for actual user interaction. This preliminary generation and ranking process allows the system to have pre-computed, high-quality response options ready for rapid deployment when contextually appropriate, reducing the perceived response time during actual use.
Solution Approach 2:
The patent generates more candidate responses than would traditionally be considered necessary (excessive action), then ranks them to identify the most relevant ones. This approach ensures high response quality by having multiple options to choose from, while the ranking mechanism efficiently filters down to the best candidates, balancing quality with processing efficiency.
Data Source
AI summary
Systems and processes for operating an intelligent automated assistant to provide a set of predicted responses are provided. An example method includes, at an electronic device having one or more processors, receiving one or more messages and analyzing the unstructured natural language information of the one or more messages. The method also includes determining, based on the analysis of the unstructured natural language information, whether one or more predicted responses are to be provided. The method further includes, in accordance with a determination that one or more predicted responses are to be provided, determining, from a plurality of sets of candidate predicted responses, one set of predicted responses to be provided to the user based on context information. The method further includes providing the determined set of one or more predicted responses to the user.