Fuzzy String Matching in Python: Intro to Fuzzywuzzy | Built In
Fuzzy String Matching in Python: Intro to Fuzzywuzzy | Built In
Apr 17, 2025
builtin.com
New in MongoDB Atlas: Lexical Prefilters for Vector Search. You can now use full analyzed text filtering (fuzzy, phrase, queryString, geo) as prefilters for $search.vectorSearch, with vector fields supported inside Lucene $search indexes. With this new capability, you'll get ✅ Advanced filtering vector search in one flow (no more knnBeta / knnVector) ⚡️ More efficient retrieval (fewer candidates = less compute) 🎯 Better precision vs post-filtering 🧠 Complex boolean logic with queryString Learn
2:21
New in MongoDB Atlas: Lexical Prefilters for Vector Search. You can now use full analyzed text filtering (fuzzy, phrase, queryString, geo) as prefilters for $search.vectorSearch, with vector fields supported inside Lucene $search indexes. With this new capability, you'll get ✅ Advanced filtering vector search in one flow (no more knnBeta / knnVector) ⚡️ More efficient retrieval (fewer candidates = less compute) 🎯 Better precision vs post-filtering 🧠 Complex boolean logic with queryString Learn
975 views3 months ago
FacebookMongoDB
Let’s talk about the future of search. What if you could combine the precision of keyword search with the semantic power of vector search, in a single query? 🚀 Introducing native hybrid search in MongoDB Atlas, now in public preview. With the new $rankFusion stage in Atlas Search, you can merge full-text and vector search results into a single ranked list using reciprocal rank fusion (RRF). That means smarter, more relevant results—without bolting on a separate vector database or search engine.
1:26
Let’s talk about the future of search. What if you could combine the precision of keyword search with the semantic power of vector search, in a single query? 🚀 Introducing native hybrid search in MongoDB Atlas, now in public preview. With the new $rankFusion stage in Atlas Search, you can merge full-text and vector search results into a single ranked list using reciprocal rank fusion (RRF). That means smarter, more relevant results—without bolting on a separate vector database or search engine.
1.4K views10 months ago
FacebookMongoDB
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