Locality-sensitive hashing

Known as: LSH, Locality Sensitive Hashing

Locality-sensitive hashing (LSH) reduces the dimensionality of high-dimensional data. LSH hashes input items so that similar items map to the same…

Papers overview

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2015

Similarity search in graph databases has been widely studied in graph query processing in recent years. With the fast…

2014

Locality sensitive hashing LSH is the most popular algorithm for approximate nearest neighbor ANN search. As LSH partitions…

2013

Locality Sensitive Hashing (LSH) has been popularly used in content-based search systems. There exist two main categories of LSH…

2012

Locality sensitive hashing (LSH) has been introduced as an indexing structure for fast large-scale data retrieval. A significant…

2012

Nearest neighbor problem has recently been a research focus, especially on large amounts of data. Locality sensitive hashing (LSH…

2011

Similarity joins are important operations with a broad range of applications. In this paper, we study the problem of vector…

Highly Cited

2010

Highly Cited

2010

Conventional subspace learning-based face recognition aims to attain low recognition errors and assumes same loss from all…

2010

In this paper, we study the problem of detecting near duplicates for high dimensional data points in an incremental manner. For…

2010

In this paper, we present DLSH Distributed Locality Sensitive Hashing, a similar-data search technology. The huge growth in the…

2009

There are many applications for the ability to find repetitions of perceptually similar sound events in generic audio recordings…