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2 results about "Locality-sensitive hashing" patented technology
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In computer science, locality-sensitive hashing (LSH) is an algorithmic technique that hashes similar input items into the same "buckets" with high probability. (The number of buckets are much smaller than the universe of possible input items.) Since similar items end up in the same buckets, this technique can be used for data clustering and nearest neighbor search. It differs from conventional hashing techniques in that hash collisions are maximized, not minimized. Alternatively, the technique can be seen as a way to reduce the dimensionality of high-dimensional data; high-dimensional input items can be reduced to low-dimensional versions while preserving relative distances between items.
Locality sensitive hashing using bitmap index
A data item identification service may use locality sensitive hashing to identify data items which are relevant to a search based on a hash of a search vector based on the search. Hashes of vectors based on data items may be stored using a set of bitmaps, where a given bitmap corresponds to a given bit position of a hash. Data items with matching or similar hashes may be related to each other. The data item identification service may perform searches by generating a hash for a search vector and comparing the hash to hashes for data items using one or more logical operations on the set of bitmaps to identify related data items.
Owner:AMAZON TECH INC
A retrieval enhancement method and system based on asymmetric locality sensitive hashing
The application discloses a retrieval enhancement method and system based on asymmetric local sensitive hashing. The retrieval enhancement method comprises the following steps: establishing a knowledge text database, including a plurality of knowledge texts; acquiring a query text, and extracting target knowledge texts related to the query text in the knowledge text database based on an asymmetric local sensitive hashing algorithm; establishing a background formula, the background formula including placeholders uniquely corresponding to the target knowledge texts and the query text, and then replacing the corresponding placeholders in the background formula with the target knowledge texts and the query text to obtain an input text; and inputting the input text into a large language model to output an answer text. The application has the characteristics of accuracy and efficiency.
Owner:HOHAI UNIV