Text Search Engine

In this tutorial, you will learn how to use Milvus, the open-source vector database, to build a text search engine.

The ML model and third-party software used include:

One major application of Milvus in the field of natural language processing (NLP) is text search engine. It is a great tool that can help users find the information they are looking for. It can even surface information that is hard to find. Text search engines compare the keywords or semantics users input against a database of texts, and then return the results that meet certain criteria.

In this tutorial, you will learn how to build a text search engine. This tutorial uses BERT to convert texts into fixed-length vectors. Milvus is used as a vector database for storage and vector similarity search. Then use MySQL to map the vector IDs generated by Milvus to the text data.

Workflow of a text search engine.
Demo of text search engine.

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