To capture the meaning and context of human language, semantic search through vectors can significantly improve the relevance of search results, leading to a better understanding of user queries. However, organizations need significant expertise and effort beyond typical software productization to achieve satisfactory information retrieval quality. This expertise includes annotating a sufficient number of queries and maintaining the models or relying on third-party models adapted to their specific domain.
Recognizing these challenges, we will discuss semantic search with dense and sparse vectors in this talk. And why you still need lexical search with hybrid retrieval for specific scenarios.