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Doug Turnbull - Staff Relevance Engineer, Shopify - Search as a constant experimentation cycle
Vector Podcast
Precision Over Fuzziness in Document Representation
BERT and similar models enhance document representation by focusing on the precision of related concepts rather than a fuzzy and broad approach. Unlike traditional dense vector representations, BERT excels at pinpointing the exact aspects of a document that are most significant, allowing for a more targeted search. In contrast, models like Word2Vec struggle with capturing the 'aboutness' of documents due to their more generalized window-based approach. BERT's ability to embed each token position individually is particularly remarkable, enabling precise matching of queries to specific parts of the document. This precision in document representation offered by BERT has the potential to revolutionize search capabilities, especially in distinguishing between similar concepts within text.
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