Vector Search & Embeddings in Java: Building Semantic Search Engines

Traditional keyword-based search is obsolete, replaced by vector search and embeddings to capture user intent. This technology powers AI applications like ChatGPT's RAG, Netflix, and Spotify. However, a gap exists between retrieval and ranking. While vector search identifies candidates, a complex ranking pipeline is required to order results by relevance. This process integrates BM25 scores, semantic similarity, category matches, and price alignment to ensure users find accurate results instead of irrelevant candidates.