Relevance feedback is a technique used in information retrieval where user interactions are utilized to improve search results based on their preferences. By analyzing the relevance of previously retrieved documents, systems can adjust and refine their algorithms to better align with the user's needs. This feedback loop enhances the effectiveness of both text indexing and retrieval models and passage retrieval and ranking, leading to more accurate and personalized search outcomes.
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