Analysis of Web Data Mining Combining Software Capability Maturity Model

Authors

  • Xiang Li School of Artificial Intelligence and Big Data, Chongqing College of Electronic Engineering; Chongqing 401331 China
  • Zijia Zhang School of Automation, Nanjing university of information science and technology; Nanjing Jiangsu 210044 China

Abstract

Based on the real-time requirements of the Java Web big data mining model and the diversity characteristics of data samples, a Java Web big data mining model for the software capability maturity model (hereinafter referred to as SCMM for short) is put forward. The calculation process for the construction of the current model is analyzed, and the construction process is divided into two stages namely the rough adjustment stage and the fine-tuning stage, according to the size of change of model vector. It is found that most of samples in the fine-tuning stage have very little influence on the calculation results. Therefore, it is not necessary to calculate the gradient of such samples in the fine-tuning stage, while the calculation results constructed previously can be used directly, thereby reducing the amount of computation and improving the computational efficiency. The
experimental results show that the proposed model can reduce the amount of computation in the model training phase by about 35% in the distributed cluster environment. In addition, the model accuracy obtained by the training is within the normal scope, and the real-time performance of the Java Web big data mining model can be effectively improved.

Keywords: Mining algorithm; Distributed System; Machine Learning; Software Capability Maturity Model; Optimization Model

Cite As

X. Li, Z. Zhang, "Analysis of Web Data Mining Combining Software Capability Maturity Model", Engineering Intelligent Systems,
vol. 27 no. 1, pp. 19-26, 2019.




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Published

2019-03-01

Issue

Vol. 27 No. 1 (2019): International Journal of Engineering Intelligent Systems

Section

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