Dynamic Query Response Interface Selection
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Solution Overview
Problem
Conventional query response systems use a statically configured response strategy, failing to adapt to query attributes and confidence levels, leading to suboptimal user interface selection for query handling.
Innovation Solution
A system that selects a query response interface based on query attributes and confidence levels, using a search result selection engine with machine learning to determine the suitability of conversational or non-conversational interfaces, and their subtypes, for presenting search results effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a statically configured response strategy is used, then system complexity is reduced, but adaptability to different query attributes and confidence levels deteriorates
Solution Approach 1:
The patent implements a dynamic interface selection mechanism that automatically chooses between conversational and non-conversational interfaces based on real-time analysis of query attributes and confidence levels. The system transitions from static configuration to dynamic adaptation by evaluating query characteristics and selecting the most appropriate interface type, thereby resolving the contradiction between system complexity and adaptability.
2Ease of operation
If a single response strategy is used for all queries, then ease of operation is improved, but response accuracy deteriorates
Solution Approach 1:
The patent applies local quality by tailoring the response interface to the specific characteristics of each query. Instead of using a uniform response strategy, the system analyzes query attributes and confidence levels to provide locally optimized responses - using conversational interfaces for ambiguous queries and non-conversational interfaces for clear, straightforward queries, thereby improving response accuracy while maintaining ease of operation.
3Device complexity
If conventional query response systems are used, then device complexity is reduced, but user satisfaction deteriorates due to suboptimal interface selection
Solution Approach 1:
The patent changes the parameter of interface selection from fixed to variable based on query attributes and confidence levels. The system evaluates multiple parameters including query clarity, confidence level, and user context to dynamically adjust the interface type, thereby improving interface selection suitability without significantly increasing device complexity through automated decision-making algorithms.
Data Source
AI summary
Techniques for system selection for query handling are disclosed. A query response selection system may receive a query from a user and determine attributes corresponding to the query and/or candidate sets of search results that may be displayed in response to the query. The system may select a response interface from one of a plurality of response interfaces for responding to the query. The plurality of response interfaces may include a conversational user interface and a non-conversational user interface. The system may display the response interface with a response to the query.