Eugene Yan • 7/20/2021

Mailbag: How to Bootstrap Labels for Relevant Docs in Search

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This article addresses a reader's question on how industry engineers obtain the 'total number of relevant documents' to evaluate search systems with metrics like Recall@K. It advises starting with a lexical search system (e.g., BM25), deploying it to collect user click data as labels, and then using that data to train and evaluate a semantic search model, avoiding the high cost of large-scale human annotation.

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#Machine Learning #Information Retrieval #Semantic Search
Mailbag: How to Bootstrap Labels for Relevant Docs in Search

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