FAQ Response System

Requirements Clarification & Assessment

1. Objective:

   • Develop a chatbot capable of responding to user queries by matching them with the most relevant FAQ from a predefined list.

2. Input/Output:

   • Input: A user query in natural language.
   • Output: The most relevant FAQ answer or a default response directing to customer support if no relevant FAQ is found.

3. Constraints:

   • Accuracy: The system should accurately match queries to FAQs with high precision.
   • Scalability: The system should handle a large number of FAQs and queries efficiently.
   • Real-time Performance: Responses should be generated in real-time or near-real-time.

4. Data Availability:

   • FAQ Dataset: A list of FAQs with corresponding answers.
   • Historical Queries: Past user queries and their matched FAQs, if available, for supervised learning.

5. Evaluation Metrics:

   • Precision & Recall: To measure the accuracy of the FAQ matching.
   • Response Time: To ensure real-time performance.
   • User Satisfaction: Feedback from users to assess the quality of responses.

6. Fallback Mechanism:

   • A mechanism to route the query to a human agent if no suitable FAQ is found.