trendingAI & ML — INTRODUCTION
Semantic Search vs Keyword Search: Which One Finds the Right Answer?
Search for “cheap laptop” and a document that only says “affordable laptop” should probably show up. Search for an exact error code, and the one document that has it should always win. No single search method handles both cases equally well.
The Quick Answer
Keyword search matches the literal words in a query against the literal words in a document — fast, precise, and exact. Semantic search converts text into embeddings and matches by meaning, so it can find relevant results even when no exact words overlap. Neither approach is strictly better — keyword search tends to win on precise identifiers (product codes, error numbers, exact names), while semantic search tends to win when a query and a document describe the same idea in different words.
What the Experts Say
Keyword search’s dominant modern algorithm, BM25, comes out of decades of information-retrieval research formalized in what’s known as the Probabilistic Relevance Framework — the same body of work that produced one of the most widely used text-retrieval and web-search ranking algorithms in existence. Semantic search, covered throughout this series via vector databases, is the newer approach — and the two are frequently combined rather than treated as competitors, precisely because each one's weaknesses are the other's strengths. See Robertson & Zaragoza, “The Probabilistic Relevance Framework: BM25 and Beyond”.
See Both Failure Modes Yourself
Try three different queries against the same small document library, and watch which search method wins — and which one quietly misses the right answer.
Fun Fact
BM25 predates modern neural search by decades, yet it remains a standard baseline that production search systems are still measured against — it’s simple, fast, and precise in exactly the situations where semantic search tends to struggle.
Test Yourself
Why would keyword search find nothing for the query "cheap laptop" even if a document says "an affordable laptop for students"?
Why can semantic search sometimes fail to prioritize an exact match for something like a specific error code?
Ready to see BM25’s actual formula worked in code, and exactly why semantic search struggles with rare or technical terms? Continue to the Intermediate level →