Text search engine is great tool that can help you and your users find the information you are looking for. It can even surface information that is hard to find. The text search engines will compare the keywords or semantics you input against a database of texts, and then return the results that meet certain criteria. To build an intelligent and lightning-fast text search engine, you need to use machine learning (ML) and artificial intelligence (AI) models to convert these texts into vectors and then store the vectors in Milvus, the open-source vector database. Then, you can use Milvus to easily conduct a vector similarity search.
Visit the github repo to learn how to build a text search engine using Milvus and the BERT model.
You can also learn more about how to use Milvus to build other systems for various application scenarios in our bootcamp repo on Github.