An Innovative Algorithm for Enhanced PDF-Based Chatbot in Domain-Specific Question Answering

Abstract

This paper introduces a novel algorithm designed to enhance the performance of PDF-based chatbots for domain-specific question answering. The proposed system integrates advanced table parsing techniques, hybrid indexing, context-aware response generation, and a continuous learning feedback loop, effectively addressing the limitations of existing approaches. We validate the effectiveness of our algorithm through a case study using a PDF document on pregnancy, demonstrating its potential applications across various specialized knowledge domains. The chatbot’s innovative features, such as advanced multimodal content processing and dynamic knowledge base updates, establish it as a powerful tool for extracting relevant information from complex documents