The rapidly growing information technology in modern days demands an efficient searching scheme to search for desired data. Locality Sensitive Hashing (LSH) is a method for searching similar data in a database. LSH achieves high accuracy and precision for locating desired data, but consumes a significant amount of memory and time. Based on LSH, this thesis presents two novel schemes for efficient and accurate data searching: Locality Sensitive Hashing-SmithWaterman (LSH-SmithWaterman) and Secure Min-wise Locality Sensitive Hashing (SMLSH). Both methods dramatically reduce the memory and time consumption and exhibit high accuracy in data searching. Simulation results demonstrate the efficiency of the two schemes in comparison with LSH. The s...
Locality sensitive hashing (LSH) was introduced by Indyk and Motwani (STOC\u2798) to give the first ...
Locality sensitive hashing (LSH) was introduced by Indyk and Motwani (STOC ‘98) to give the first su...
En este artículo proporcionamos una descripción general del hash sensible a la ubicación (LSH) utili...
Many modern applications of AI such as web search, mobile browsing, image processing, and natural la...
Locality Sensitive Hashing (LSH) is widely recognized as one of the most promising approaches to sim...
Locality-Sensitive Hashing (LSH) is widely used to solve approximate nearest neighbor search problem...
Among many solutions to the high-dimensional approximate nearest neighbor (ANN) search problem, loca...
International audienceIt is well known that high-dimensional nearest-neighbor retrieval is very expe...
Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest neighbo...
The need to locate the k-nearest data points with respect to a given query point in a multi- and hig...
It is well known that high-dimensional nearest-neighbor retrieval is very expensive. Many signal pro...
This lecture note describes a technique known as locality-sensitive hashing (LSH) that allows one to...
International audienceIt is well known that high-dimensional nearest-neighbor retrieval is very expe...
Locality Sensitive Hashing (LSH) is an effective method to index a set of points such that we can ef...
Many modern applications of AI such as web search, mobile browsing, image processing, and natural la...
Locality sensitive hashing (LSH) was introduced by Indyk and Motwani (STOC\u2798) to give the first ...
Locality sensitive hashing (LSH) was introduced by Indyk and Motwani (STOC ‘98) to give the first su...
En este artículo proporcionamos una descripción general del hash sensible a la ubicación (LSH) utili...
Many modern applications of AI such as web search, mobile browsing, image processing, and natural la...
Locality Sensitive Hashing (LSH) is widely recognized as one of the most promising approaches to sim...
Locality-Sensitive Hashing (LSH) is widely used to solve approximate nearest neighbor search problem...
Among many solutions to the high-dimensional approximate nearest neighbor (ANN) search problem, loca...
International audienceIt is well known that high-dimensional nearest-neighbor retrieval is very expe...
Locality Sensitive Hashing (LSH) is one of the most promising techniques for solving nearest neighbo...
The need to locate the k-nearest data points with respect to a given query point in a multi- and hig...
It is well known that high-dimensional nearest-neighbor retrieval is very expensive. Many signal pro...
This lecture note describes a technique known as locality-sensitive hashing (LSH) that allows one to...
International audienceIt is well known that high-dimensional nearest-neighbor retrieval is very expe...
Locality Sensitive Hashing (LSH) is an effective method to index a set of points such that we can ef...
Many modern applications of AI such as web search, mobile browsing, image processing, and natural la...
Locality sensitive hashing (LSH) was introduced by Indyk and Motwani (STOC\u2798) to give the first ...
Locality sensitive hashing (LSH) was introduced by Indyk and Motwani (STOC ‘98) to give the first su...
En este artículo proporcionamos una descripción general del hash sensible a la ubicación (LSH) utili...