Milvus is an open-source vector database designed for similarity search of high-dimensional vectors, making it ideal for applications like semantic search, recommendation systems, and AI-powered search. It supports indexing and searching large volumes of vectors, typically produced by machine learning models like deep neural networks.
In IR, Milvus is used to manage vector embeddings from text, images, audio, or other unstructured data. By converting data into vectors, Milvus allows for fast and efficient similarity searches based on proximity, making it a powerful tool for semantic search, where traditional keyword-based approaches may fall short.
Milvus supports multiple indexing algorithms, such as IVF (inverted file) and HNSW (hierarchical navigable small world), allowing users to optimize search performance. It can handle billions of vectors and scale horizontally, making it suitable for large-scale IR applications in industries such as e-commerce, healthcare, and finance.