基于云计算的大数据并行搜索聚类算法研究  

Research on big data parallel search clustering algorithm based on Cloud Computing

作　　者：王玉贤[1] WANG Yuxian(Guangdong Songshan Polytechnic College,Guangdong 512126f China)

机构地区：[1]广东松山职业技术学院,广东韶关512126

出　　处：《自动化与仪器仪表》2021年第10期33-36,共4页Automation & Instrumentation

基　　金：依托项目广东省教育厅2020年重点科研平台项目(No.2020ZDZX3119)。

摘　　要：随着互联网技术的不断发展,网络中的数据爆炸式增加。利用数据处理技术挖掘大数据背后的价值成为当前的数据领域研究重点。当前使用中的大数据并行搜索聚类算法在数据聚类分析方向使用技术较为落后,造成数据处理同步率较低的问题。针对此情况,设计基于云计算的大数据并行搜索聚类算法。将分词词典应用到数据搜索,设计大数据搜索引擎。通过数据矩阵的形式对网络中的原始数据展开处理,使用相似度计算方法,完成数据聚类分析。根据当前数据处理需求,设定数据并行处理约束条件。将此条件与大数据搜索引擎及聚类分析方法相结合,至此,基于云计算的大数据并行搜索聚类算法设计完成。构建算例应用环节对此算法使用效果展开测试。实验结果表明此方法可有效避免当前算法在使用中出现的问题,提升数据分析效果。With the continuous development of Internet technology, the data explosion in the network. Using data processing technology to mine the value behind big data has become the focus of current data research. The current big data parallel search clustering algorithm is backward in the direction of data clustering analysis, resulting in the problem of low synchronization rate of data processing. In view of this situation, a big data parallel search clustering algorithm based on cloud computing is designed. Apply word segmentation dictionary to data search, design big data search engine. The original data in the network is processed in the form of data matrix, and the similarity calculation method is used to complete the data clustering analysis. According to the current data processing requirements, the constraints of data parallel processing are set. By combining this condition with big data search engine and clustering analysis method, the design of big data parallel search clustering algorithm based on cloud computing is completed. The application of the algorithm is tested in the construction of an example. Experimental results show that this method can effectively avoid the problems in the use of the current algorithm and improve the effect of data analysis.

关 键 词：云计算 大数据 聚类分析 并行化运行 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]