Virtual Assistant Cognitive Model for Incomplete Problem Descriptions
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Solution Overview
Problem
Conventional virtual assistants often prematurely process user input, leading to irrelevant responses due to incomplete problem descriptions, as they struggle to identify when a user has finished providing details about their issue, especially in cases with poor grammar or incomplete sentences.
Innovation Solution
A computer-implemented method that applies a cognitive model to determine the completeness of problem descriptions, prompting users for additional information if necessary, and uses recurrent neural networks and classifiers to identify intents behind user input, ensuring a complete problem description is provided before generating a response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If the virtual assistant processes user input immediately, then the response time is reduced, but the accuracy of the response deteriorates due to incomplete problem descriptions
Solution Approach 1:
The system performs preliminary analysis of the user input to determine completeness before processing. The cognitive model evaluates whether the problem description is sufficient upfront, and only then proceeds to generate a response or request additional information, preventing premature processing of incomplete inputs
Solution Approach 2:
The system implements a feedback mechanism where the cognitive model continuously monitors incoming user statements and provides feedback on completeness. When the input is determined to be incomplete, the system prompts the user to provide additional information before generating a response, ensuring accuracy without excessive delay
2Measurement precision
If the virtual assistant waits for complete problem descriptions, then the accuracy of the response is improved, but the response time increases due to waiting for additional user input
Solution Approach 1:
The system dynamically adjusts its processing behavior based on the completeness of user input. The cognitive model continuously evaluates incoming statements and transitions between waiting for more input and generating responses based on the current completeness assessment, optimizing the balance between accuracy and response time
Solution Approach 2:
The system performs preliminary evaluation of each user statement to assess completeness before deciding whether to wait for more input or generate a response. This upfront assessment prevents unnecessary waiting while ensuring that responses are only generated when sufficient information is available
3Measurement precision
If the virtual assistant uses a cognitive model to analyze complete problem descriptions, then the relevance of the response is improved, but the system complexity increases
Solution Approach 1:
The cognitive model serves as an intermediary component that bridges user input and the response generation system. It analyzes the completeness of problem descriptions and controls the flow of information to the intent recognition and response formulation modules, improving relevance while containing complexity through modular architecture
Solution Approach 2:
The system segments the processing pipeline into distinct modules: a cognitive model for completeness analysis, an intent recognition module, and a response generation module. This segmentation allows each component to specialize in its function, improving overall relevance while managing system complexity through modularity
4Loss of information
If the virtual assistant prompts users for additional information, then the completeness of the problem description is improved, but the interaction duration increases
Solution Approach 1:
The system applies partial action by prompting users for only the specific additional information needed to complete the problem description, rather than requesting all possible information. The cognitive model identifies precisely what is missing and requests only that, minimizing interaction duration while ensuring completeness
Data Source
AI summary
User input handling by a virtual assistant includes receiving a sequence of natural language statements provided by a user to a virtual assistant, applying a cognitive model to the sequence of statements and determining whether the sequence of statements provides a complete problem description, by the user, to which the virtual assistant is to respond in assisting the user address a problem that the user experiences, prompting the user to provide an additional one or more statements to complete the problem description, based on completing the problem description, formulating and providing a response to the user based on a determined intent of the complete problem description, and monitoring input by the user based on providing the response, the input informing feedback for further training of the cognitive model to identify whether statement sequences provide complete or incomplete problem descriptions.