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The amount of data is exploding with the development of Internet and multimedia technology. Rapid retrieval of mass data is becoming more and more important. To meet the demand of the rapid retrieval, many approximate nearest neighobor methods have been proposed to accelerate the exhaustive search process. Hashing is such an example with great balance of time and accuracy. Hashing methods achieve...
In information retrieval, efficient accomplishing the nearest neighbor search on large scale database is a great challenge. Hashing based indexing methods represent each data instance as a binary string to retrieve the approximate nearest neighbors. In this paper, we present a semi-randomized hashing approach to preserve the Euclidean distance by binary codes. Euclidean distance preserving is a classic...
The p-stable distribution is traditionally used for data-independent hashing. In this paper, we describe how to perform data-dependent hashing based on p-stable distribution. We commence by formulating the Euclidean distance preserving property in terms of variance estimation. Based on this property, we develop a projection method, which maps the original data to arbitrary dimensional vectors. Each...
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