Big data mining analysis method based on cloud computing
Qing Qiu Cai,Hong Gang Cui,Hao Tang +2 more
- 03 Aug 2017
- Vol. 1864, Iss: 1, pp 020028
TL;DR: The meaning and characteristics of cloud computing, the advantages of using cloud computing technology to realize data mining, the mining algorithm of association rules based on MapReduce parallel processing architecture, and the algorithm of parallel association rule mining based on cloud computing platform are introduced.
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Abstract: Information explosion era, large data super-large, discrete and non-(semi) structured features have gone far beyond the traditional data management can carry the scope of the way. With the arrival of the cloud computing era, cloud computing provides a new technical way to analyze the massive data mining, which can effectively solve the problem that the traditional data mining method cannot adapt to massive data mining. This paper introduces the meaning and characteristics of cloud computing, analyzes the advantages of using cloud computing technology to realize data mining, designs the mining algorithm of association rules based on MapReduce parallel processing architecture, and carries out the experimental verification. The algorithm of parallel association rule mining based on cloud computing platform can greatly improve the execution speed of data mining.
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Citations
Research on Parallel Adaptive Canopy-K-Means Clustering Algorithm for Big Data Mining Based on Cloud Platform
TL;DR: This paper proposes a parallel adaptive Canopy-K-means algorithm, which can be used in cloud computing framework to determine the distance threshold parameter T2 adaptively based on statistical method.
Data mining algorithm based on cloud computing
Y. J. Hao
Abstract: The data mining algorithm based on cloud computing is studied and analyzed in this paper. Firstly, the research status and background of the data mining algorithms based on cloud computing are introduced briefly. Secondly, the design of Hash algorithm under cellular neural network is introduced which is needed in this paper. Next, the design of wavelet data compression algorithm for wireless sensor networks is described. Finally, the experimental results and the optimization similarity analysis are obtained. The analysis results show that the data mining algorithm based on cloud computing constructed in this paper plays an important role in data mining, and can improve the data mining algorithm of cloud computing and the development level of cloud computing technology and big data technology to some extent.
Bionic Optimized Clustering Data Mining Algorithm Based on Cloud Computing Platform
Yan-ping SHEN,Su-hang GU,Li-xia ZHENG +2 more
TL;DR: This study proposes a bionic optimized clustering algorithm for cloud computing platforms, combining wolf pack optimization with similarity clustering to improve data mining effectiveness and clustering performance, particularly for large-scale and high-dimensional datasets.
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