We propose an approximate computation technique for inter-object distances for binary data sets. Our approach is based on the locality sensitive hashing, scales up with the number ...
Indexing high-dimensional data for efficient nearest-neighbor searches poses interesting research challenges. It is well known that when data dimension is high, the search time can...
Similarity search has been widely studied in peer-to-peer environments. In this paper, we propose the Bounded Locality Sensitive Hashing (Bounded LSH) method for similarity search...
An efficient indexing method is essential for content-based image retrieval with the exponential growth in large-scale videos and photos. Recently, hash-based methods (e.g., local...
Locality Sensitive Hashing (LSH) is widely used for efficient retrieval of candidate matches in very large audio, video, and image systems. However, extremely large reference dat...