基于数据挖掘技术的云环境服务分类算法

Service classification algorithm of cloud environment computing based on data mining technology

为了提高Web服务的分类效果,提出了一种基于数据挖掘技术的云环境Web服务分类算法。首先提取服务特征向量,并进行相应预处理得到服务特征向量集,然后采用最小二乘支持向量机训练特征向量集,并采用萤火虫算法优化最小二乘支持向量机参数,建立最优的服务分类模型,最后采用标准数据进行仿真实验,对本文算法性能进行测试。仿真实验结果表明,相对于其它Web服务分类算法,本文算法不仅提高了Web服务分类的精度,而且提高了Web服务分类效率。

In order to improve the classification effect of the Web service,a web service classification algorithm in cloud computing based on data mining technology is proposed in this paper. Firstly,the feature vectors of service are extracted and feature vector set is obtained by pretreatment,and then least squares support vector machine is used to train feature vector set in which parameters are optimized by glowworm swarm optimization algorithm and the optimal service classification model is established,the standard data is used to by simulation experiment to test the performance of the algorithm. Simulation results show that,compared with other Web service classifications algorithms,the proposed algorithm can improve the accuracy and efficiency of Web service classification.