The High Cost of Keyword Search

Semantic search, driven by advancements in natural language processing and neural networks, is revolutionizing information retrieval by allowing systems to understand language beyond traditional keyword algorithms like TF-IDF and BM25. This technology enables the retrieval of a broader range of relevant content with greater precision, as seen in platforms like Amazon Kendra and Microsoft Semantic Search. A practical demonstration of semantic search is shown using Vectara's platform, which supports multilingual indexing and searching, as illustrated with a collection of hotel reviews from San Francisco. By converting reviews into JSON documents and indexing them, the system allows queries to return contextually relevant results, even when dealing with misspellings or lacking exact keyword matches, through vectorization and embeddings. The promise of semantic search extends across various applications, such as e-commerce and customer support, by enhancing user engagement through more relevant and meaningful search outcomes, reflecting a shift in user expectations toward natural language interactions.