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  • 标题:Evaluating Connection in Internet of Things Using Big Data Fusion Pattern
  • 本地全文:下载
  • 作者:Xu Hong ; Hu Ruo
  • 期刊名称:Journal of Software Engineering
  • 印刷版ISSN:1819-4311
  • 电子版ISSN:2152-0941
  • 出版年度:2017
  • 卷号:11
  • 期号:1
  • 页码:72-77
  • DOI:10.3923/jse.2017.72.77
  • 出版社:Academic Journals Inc., USA
  • 摘要:Objective: The purpose of the study is to evaluate the relationships among nodes in the network. Materials and Methods: The nodes of the internet of things like mix-linker currently are one of successful internet services just after large websites such as Baidu, Tencent and trading website like TaoBao. Internet of things is widely accepted gradually. Results: Hence, the main finding is that various patterns are exploited for big data evaluating, which the best method was performed to combine all of possible conditions and relationships along with using intelligent feedback model. The results shows that this study is efficiently to assess the relationship of a node with a new node using big data on mix-linker node. Conclusion: In this study, it got about 86% effective evaluating about the conclusion, which are get by using big data fusion patterns.
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