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Improve semantic search relevance with analytics and machine learning

The rise of semantic search engines has made search easier for many users. Semantic search uses ML to understand the meaning of queries, and improves the usefulness of search by understanding the intent and contextual meaning of those terms by bringing results that are more relevant than text search. This session covers the importance of search relevance, semantic search, and the underlying architecture. We demonstrate how to build a semantic search engine and improve search relevance with Amazon SageMaker and Amazon OpenSearch Service. Download slides »

Speaker: Kamal Manchanda, Solutions Architect, AWS India