99sbr/semantic-search-with-sbert
Build Semantic Search with S-BERT and Fine-tune your model in unsupervised way
Quickly find the most relevant documents in a large collection by understanding the meaning behind your search queries, rather than just keywords. You input a question or search term, and the system outputs a ranked list of documents that are semantically similar. This is for researchers, analysts, or anyone who needs to efficiently retrieve information from extensive text datasets like reports, articles, or customer feedback.
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Use this if you need to find information based on the true meaning of your query, even if the exact keywords aren't present in the documents.
Not ideal if your search needs are simple keyword matching or if your document collection is very small and doesn't require deep semantic understanding.
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Last pushed
Apr 26, 2022
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