Knowledge Graphs & Semantic AI › Semantic Search
What are common mistakes to avoid with Semantic Search
IntermediateAnswer
A common mistake with Semantic Search is applying it without fully understanding the underlying data or problem, which often leads to weak or misleading results. Skipping proper testing before relying on it in a real project is another frequent error.
Real-world example A semantic search engine can return relevant results for a search about affordable laptops even if the exact word affordable does not appear in the matching product description.