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Parallelization method for DENCLUE algorithm

An algorithm and computing node technology, applied in the field of parallelization of the DENCLUE algorithm, can solve problems that are difficult to adapt to large-scale data clustering analysis scenarios

Active Publication Date: 2018-11-27
UNIV OF ELECTRONIC SCI & TECH OF CHINA
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Problems solved by technology

Therefore, the original DENCLUE algorithm is difficult to adapt to the cluster analysis scenario of large-scale data

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  • Parallelization method for DENCLUE algorithm
  • Parallelization method for DENCLUE algorithm
  • Parallelization method for DENCLUE algorithm

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[0027] In order to make the object, technical solution and advantages of the present invention more clear and definite, the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0028] The overall flow framework of the present invention is as follows figure 1 As shown, the flow chart of data mapping and grid division represented by steps S1-S3 is as follows figure 2 shown.

[0029] S1: Divide the original data, and divide the original data into the same number of data blocks according to the number of computing nodes.

[0030] S11: According to the number n of computing nodes, the original data set is divided into n sub-data sets on average from the starting position, and sent to each node in the form of subseti for simple sampling, and each sampling generate...

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Abstract

The invention provides a parallelization method for a DENCLUE algorithm. The method can be used for the environment where large-scale data clustering analysis is performed. Compared with a traditionalcentralized execution method, the improved parallelization clustering method for the DENCLUE algorithm realizes a higher data processing speed. The method mainly includes the following steps that 1,original data is divided; 2, grid association mappings in data space are established in parallel; 3, a global grid association mapping is generated; 4, mining and clustering are performed in parallel.Through the parallelization method for the DENCLUE algorithm, the data dividing speed and final clustering speed are effectively increased, and the speed of executing the algorithm is increased.

Description

technical field [0001] The invention belongs to the field of data clustering algorithms, in particular to a parallelization method of the DENCLUE algorithm. Background technique [0002] With the rapid development of related technologies, the system and software functions are continuously improved and enhanced, and the information collected during operation, such as log records and monitoring data, is gradually developing towards high-dimensional and massive growth. The important issue is how to discover the valuable information hidden in these data. [0003] Data mining is an important means to discover the inherent laws of data and extract key information. As an important data mining technology, clustering classifies data according to similarity, so that the similarity of data in the same class is high, while the similarity of data between classes is low. [0004] The DENCLUE algorithm is a density clustering method proposed by Alexander Hinneburg et al. in 1998, which i...

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Application Information

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IPC IPC(8): G06F17/30G06N99/00
Inventor 罗光春陈爱国段贵多赵太银李尧
Owner UNIV OF ELECTRONIC SCI & TECH OF CHINA
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