👉 Relevance engineering is a critical process in information retrieval and machine learning that focuses on enhancing the relevance of search results or recommendations by aligning them more closely with user intent and context. It involves a combination of techniques such as query expansion, semantic analysis, and ranking adjustments to ensure that the most pertinent information is surfaced first. By understanding user needs through natural language processing and leveraging contextual cues, relevance engineering aims to improve user satisfaction and engagement by delivering more accurate and useful outcomes. This process is essential in environments where information overload is common, such as search engines, recommendation systems, and digital content platforms.
