DSSM (Deep Structured Semantic Model) in Search and Retrieval Systems is a deep learning approach that improves how search engines understand and match user queries with relevant documents. It transforms both queries and documents into dense vector representations, enabling semantic matching based on meaning rather than exact keywords. This helps retrieval systems deliver more accurate and context-aware results, even for ambiguous or complex searches. DSSM improves ranking quality by capturing deeper relationships between words and phrases. It is widely used in modern search systems to enhance relevance and user satisfaction.
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