Unverified50% confidenceFactExact time
The content understanding of Mavis File Manager relies on local vector indexing technology, converting file content and user queries into high-dimensional vectors and retrieving semantically closest files through similarity computation.
1
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50%
Confidence
Long-term
Relevance
9/22/2026
First Seen
Sources
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Related Claims
VerifiedVector databases such as FAISS, Chroma, and Weaviate build indexes by encoding text as high-dimensional vectors, enabling semantic similarity retrieval in milliseconds.69% similarUnverifiedVector databases (such as Milvus, Chroma, and Weaviate) use approximate nearest neighbor algorithms to find content that is similar in meaning rather than identical in wording.68% similarUnverifiedThe knowledge base relies on RAG (Retrieval-Augmented Generation) technology at its foundation, slicing private documents and converting them into high-dimensional vectors via an Embedding model for storage in a vector database.66% similarUnverified父子块策略将文档同时索引为大块和小块，检索时用小块精准定位，生成时返回大块提供完整上下文66% similar
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