AI Question Classification for Responder Matching
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Solution Overview
Problem
Existing service centers require users to perform multiple interactions to find a suitable responder, leading to potential errors and inefficiencies, as they often rely on manual selection methods that can be cumbersome and result in poor user experience.
Innovation Solution
A method and device utilizing artificial intelligence to classify user questions by acquiring text content, performing word segmentation, generating hidden representation vectors, and determining a target responder based on a preset classification model, thereby simplifying the process and reducing user interactions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual selection methods are used for users to find responders, then users can select responders, but the number of interactions increases and user experience deteriorates
Solution Approach 1:
The system performs automatic question classification and responder matching without requiring user interactions. The classification model automatically analyzes user questions and assigns them to appropriate responders, eliminating the need for users to manually navigate menus or perform multiple selection steps.
Solution Approach 2:
The patent replaces the mechanical manual selection process with an intelligent automated system. Instead of users manually selecting responders through dial keyboards or multilevel menus, an AI-based classification model automatically processes the question and determines the appropriate responder assignment.
2Ease of operation
If manual selection methods are used for users to find responders, then users can select responders, but the complexity of the system increases
Solution Approach 1:
The patent extracts the complex classification and matching logic from the user interaction process and places it in the background system. The user-facing interface remains simple while the backend contains the sophisticated neural network classification model that handles the complexity of question analysis and responder matching.
3Productivity
If automatic classification is implemented, then user interactions are reduced, but the complexity of the classification model increases
Solution Approach 1:
The classification model is trained in advance on large datasets to learn patterns and relationships between different question types and appropriate responders. This preliminary training phase allows the model to perform accurate automatic classification during actual operation without requiring complex real-time processing or user interactions.
Data Source
AI summary
Embodiments of the present disclosure disclose a method and a device for classifying questions based on artificial intelligence. The method includes: acquiring text content of a question input by a user, and performing a word segmentation process on the text content to obtain a plurality of segmentations; acquiring hidden representation vectors of the plurality of segmentations; generating a first vector of the text content according to the hidden representation vectors; and determining a target responder corresponding to the question according to the first vector and a preset classification model, and appointing the target responder to the user. The method may simplify operation steps, reduce interactions between a user and a service center, and improve efficiency of the service center.