In information retrieval (IR), relevance refers to the degree to which a document or item satisfies the informational needs of a user query. It is a subjective measure that can vary based on factors like the user's intent, context, and expectations. A relevant document provides useful, meaningful, or pertinent information in relation to the query.
Relevance is typically measured using metrics such as precision, recall, and F1-score, which evaluate how well the system retrieves documents that are both accurate and comprehensive. These metrics help quantify how relevant the retrieved documents are compared to all possible relevant documents in the corpus.
Since relevance is user-dependent, IR systems often personalize search results, considering factors like past behavior, preferences, or location, to enhance relevance for individual users. Understanding and measuring relevance is crucial for designing effective IR systems.