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Similarity storage design method based on spectral hashing

A design method and similarity technology, applied in the field of similarity storage design based on spectral hash, can solve the problem of high system query overhead, and achieve the effect of avoiding overloading

Active Publication Date: 2016-05-04
NANJING UNIV OF POSTS & TELECOMM
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Problems solved by technology

[0004] In view of the deficiencies in the above technologies, the present invention proposes a similarity storage design method based on spectral hashing to ensure that similar node servers contain similar original spatial data, so as to solve the problem of excessive system query overhead during similarity queries

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  • Similarity storage design method based on spectral hashing
  • Similarity storage design method based on spectral hashing
  • Similarity storage design method based on spectral hashing

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Embodiment Construction

[0018] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0019] Such as figure 1 Shown is the design method of similarity storage based on spectral hashing. The method is mainly divided into three levels, namely: data mapping using spectral hashing, data mapping method, and construction of Chord. The specific implementation steps include the following:

[0020] (1) Data mapping using spectral hashing

[0021] Spectral hashing integrates spectral analysis technology into hash functions, and uses the constructed new hash functions to process high-dimensional data. Spectral hashing needs to perform spectral analysis on high-dimensional data samples first...

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Abstract

The invention discloses a similarity storage design method based on spectral hashing. A spectral hashing method is combined with a data mapping algorithm, such that different kinds of high-dimensional data can be rapidly mapped in a distributed node space based on a distributed hash table. The hash table is distributed on a Chord ring to construct; simultaneously, corresponding hash buckets are mapped on the Chord ring by utilizing a designed novel data mapping algorithm; therefore, the more similar data in the two hash buckets are, the closer the two hash buckets on the Chord ring are; furthermore, the conception of virtual buckets is provided; each physical node server is regarded as one or more virtual buckets; the load of each virtual bucket is dynamically adjusted, such that the node on the Chord ring satisfies the load balance; the problem that the system query overhead is too high when the similarity query is carried out can be solved; and the data query efficiency is increased.

Description

technical field [0001] The invention relates to the technical fields of storage and machine learning, in particular to a spectral hash-based similarity storage design method. Background technique [0002] Spectral Hashing (SH) obtains a corresponding hash function by training the sample data set, and then uses this function to reduce the dimensionality of high-dimensional data points to generate low-dimensional binary data. Spectral hashing can not only improve the query efficiency, but also keep the sample distance calculated in the Hamming space consistent with the sample distance calculated in the original high-dimensional space. Spectral hashing is better than other hashing methods, such as Locality-Sensitive Hashing (LSH), in reducing hash bits by approximate search. [0003] The general hash bucket definition means that the original spatial data is mapped to the corresponding bucket through a certain hash method, and each hash bucket contains the original data with th...

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/2228G06F16/2255G06F16/2462G06F16/27
Inventor 胡海峰黄赛金吴建盛
Owner NANJING UNIV OF POSTS & TELECOMM
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