Question answering system is a common real world application that belongs to the field of natural language processing. Typical QA systems include online customer service systems, QA chatbots, and more. Most question answering systems can be classified as: generative or retrieval, single-round or multi-round, open-domain or specific question answering systems.
Milvus, the open-source vector database, can be used to build question answering systems, especially chatbots that use natural language processing (NLP) to simulate a live operator, answer questions, route users to relevant information, and reduce labor costs. By combining Milvus with BERT, a machine learning (ML) model developed for NLP pre-training, chatbots can understand semantic language.
You can also learn more about how to use Milvus to build other systems for various application scenarios in our bootcamp repo on Github.