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Data mining for the internet of things: Literature review and challenges

  • Feng Chen
  • , Pan Deng
  • , Jiafu Wan*
  • , Daqiang Zhang
  • , Athanasios V. Vasilakos
  • , Xiaohui Rong
  • *此作品的通讯作者
  • CAS - Institute of Software
  • South China University of Technology
  • Tongji University
  • Luleå University of Technology
  • Chinese Academy of Civil Aviation Science and Technology

科研成果: 期刊稿件文献综述同行评审

摘要

The massive data generated by the Internet of Things (IoT) are considered of high business value, and data mining algorithms can be applied to IoT to extract hidden information from data. In this paper, we give a systematic way to review data mining in knowledge view, technique view, and application view, including classification, clustering, association analysis, time series analysis and outlier analysis. And the latest application cases are also surveyed. As more and more devices connected to IoT, large volume of data should be analyzed, the latest algorithms should be modified to apply to big data. We reviewed these algorithms and discussed challenges and open research issues. At last a suggested big data mining system is proposed.

源语言英语
文章编号431047
期刊International Journal of Distributed Sensor Networks
2015
DOI
出版状态已出版 - 2015
已对外发布

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