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Implementation of Web Mining Algorithm Based on Cloud Computing

机译：基于云计算的Web挖掘算法的实现

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摘要

The rapid growth of the Internet exceeds all expectations. The analysis and mining of huge amounts of web data is facing a bottleneck in computing power and storage space. Through the use of cloud computing technology, we can facilitate the network access to powerful computing power, storage capacity and infrastructure. Cloud computing can effectively solve the problems by providing a data processing storage center of high reliability and scalability, which will improve the ability to process web data and reduce the requirements of the terminal devices. This paper studies web mining algorithms in a cloud computing environment. The web data mining algorithm and the MapReduce programming model are combined. We study the web mining techniques, especially the K-centers clustering algorithm, explore the combination of web mining algorithms and cloud computing technology and improve the data mining algorithms to adapt to the analysis and processing of mass web data based on cloud computing platforms. Our study constructs a distributed cloud environment using a Hadoop framework. In the experimental environment, we analyze the impact on computational performance by setting different block size parameters. Here, the block size determines the number that the pending data file is split, and the corresponding scale and amount of parallel calculation.
机译：互联网的快速发展超出了所有预期。对大量Web数据的分析和挖掘正面临计算能力和存储空间的瓶颈。通过使用云计算技术，我们可以促进网络访问强大的计算能力，存储容量和基础架构。云计算可以通过提供高可靠性和可扩展性的数据处理存储中心来有效地解决这些问题，这将提高处理Web数据的能力并降低终端设备的需求。本文研究了云计算环境中的Web挖掘算法。将Web数据挖掘算法和MapReduce编程模型结合在一起。我们研究了Web挖掘技术，特别是K-centers聚类算法，探索了Web挖掘算法与云计算技术的结合，并改进了数据挖掘算法，以适应基于云计算平台的海量Web数据的分析和处理。我们的研究使用Hadoop框架构建了一个分布式云环境。在实验环境中，我们通过设置不同的块大小参数来分析对计算性能的影响。在这里，块大小决定了待处理数据文件的分割数量，以及相应的并行计算规模和数量。

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  • 来源
    《Intelligent automation and soft computing》 |2017年第4期|599-604|共6页
  • 作者

    Wu Wei; Chen Yanming; Seng Dewen;

  • 作者单位

    Zhejiang Univ Water Resources & Elect Power, Coll Informat Engn & Art Design, Hangzhou, Zhejiang, Peoples R China;

    Zhejiang Univ Water Resources & Elect Power, Supervis Dept, Hangzhou, Zhejiang, Peoples R China;

    Hangzhou Dianzi Univ, Sch Comp Sci & Technol, Hangzhou, Zhejiang, Peoples R China|Minist Educ, Key Lab Complex Syst Modeling & Simulat, Hangzhou, Zhejiang, Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Web mining; Cloud computing; Hadoop; Map Reduce;

    机译：Web挖掘;云计算;Hadoop;Map Reduce;

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