Goal-oriented dialog system dynamic service provider selection
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Solution Overview
Problem
Current dialog processing systems, particularly goal-oriented multi-turn systems, face challenges in efficiently selecting and presenting the most suitable service providers to users based on their requests, often relying on static preferences and lacking dynamic adaptation to user feedback and changing circumstances.
Innovation Solution
A system that processes user inputs through speech recognition and natural language understanding to determine user intents and select appropriate service providers by evaluating request-to-handle scores, which consider performance goals, incentive values, and user satisfaction ratings, dynamically updating search criteria and presenting multiple service options to users.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If the system uses static preferences for service provider selection, then the system complexity is reduced, but the adaptability to user feedback and changing circumstances deteriorates
Solution Approach 1:
The patent implements dynamic service provider selection by computing request-to-handle scores in real-time based on current user feedback, performance metrics, and contextual factors. The system continuously updates service provider rankings rather than relying on static preferences, enabling adaptation to changing user needs and circumstances while maintaining manageable complexity through automated scoring mechanisms.
Solution Approach 2:
The system incorporates user feedback loops where user responses, satisfaction ratings, and interaction patterns are continuously collected and fed back into the request-to-handle score calculation. This feedback mechanism allows the system to learn from user preferences and adjust service provider selections dynamically, improving adaptability without proportionally increasing system complexity.
2Adaptability or versatility
If the system evaluates multiple service providers with dynamic scoring, then the adaptability improves, but the processing time and computational resources increase
Solution Approach 1:
The system performs preliminary actions by pre-computing and caching baseline service provider metrics, historical performance data, and contextual information before user requests arrive. This pre-processing allows the real-time request-to-handle score calculation to focus only on updating scores based on current user feedback, significantly reducing processing time while maintaining dynamic adaptation capabilities.
Solution Approach 2:
The patent optimizes processing efficiency by dynamically adjusting calculation parameters such as the weight of different feedback factors, the number of service providers evaluated, and the depth of historical data considered. These parameter changes allow the system to balance adaptability with processing speed, reducing computational overhead while maintaining effective dynamic scoring.
3Reliability
If the system presents multiple service options to users, then the user satisfaction improves, but the complexity of dialog management increases
Solution Approach 1:
The system segments the service provider selection process into distinct components: initial filtering based on request-to-handle scores, ranking of filtered providers, and selective presentation to users. This segmentation allows the dialog management system to handle multiple service options systematically, improving user satisfaction through comprehensive choices while keeping dialog management complexity manageable through structured processing stages.
Solution Approach 2:
The patent applies local quality by tailoring the presentation of multiple service options to specific user contexts, preferences, and historical behaviors. Rather than uniformly presenting all possible options, the system selectively displays the most relevant service providers based on localized user characteristics and current dialog state, improving user satisfaction while reducing dialog management complexity through context-aware filtering.
Data Source
AI summary
A dialog system receives a user request corresponding to a dialog with a user. The dialog system processes the user request to determine multiple service providers capable of responding to the user request. The dialog system selects one service provider based on a request-to-handle score, and selects another service provider based on a satisfaction rating. The dialog system updates the dialog state based on further input provided by the user to determine an output responsive to the user request.