Locality-Sensitive Hashing (LSH) is a technique used to reduce the dimensionality of data while preserving the locality of points in a high-dimensional space. It is especially useful for tasks like nearest neighbor search and similarity detection in large datasets. ### Key Features of LSH: 1. **Locality Preservation**: LSH maps similar input items to the same "buckets" with high probability, while dissimilar items are mapped to different buckets.
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