Information Retrieval Chatbot on Military Policies and Standards

Abstract

In the Canadian Armed Forces (CAF), navigating through extensive policies and standards can be a challenging task. To address the need for streamlined access to these vital documents, this paper explores the usage of artificial intelligence (AI) and natural language processing (NLP) to create a question-answering chatbot. This chatbot is specifically tailored to pinpoint and retrieve specific passages from policy documents in response to user queries. Our approach involved first developing a comprehensive and systematic data collection technique for parsing the multi-formatted policy and standard documents. Following this, we implemented an advanced NLP-based information retrieval system to provide the most relevant answers to users’ questions. Preliminary user evaluations showcased a promising accuracy rate of 88.46%. Even though this chatbot is designed to operate on military policy documents, it can be extended for similar use cases to automate information retrieval from long documents.