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arXiv 1807.02564cs.NIcs.NE
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数据采掘技术在车载Ad hoc网络中的应用

Applications of Data Mining Techniques for Vehicular Ad hoc Networks

Mohammed AL Zamil, Samer Samarah

摘要:

由于车辆自组织网络(VANESTs)的最新进展,智能应用程序已经将从这些网络生成的数据整合到提供生活质量服务中。在本文中,我们已经提出了分类的数据采掘技术,已应用于这一领域,除了这些技术的分类。我们的贡献是突出文献中的研究方法论,并允许使用不同的特征进行比较。建议的分类法涵盖基本的数据采掘技术,如:预处理,离群值检测,聚类和分类的数据。此外,它还涵盖了文献中的集中式、分布式、离线和在线技术。

英文摘要:

Due to the recent advances in vehicular ad hoc networks (VANETs), smart applications have been incorporating the data generated from these networks to provide quality of life services. In this paper, we have proposed taxonomy of data mining techniques that have been applied in this domain in addition to a classification of these techniques. Our contribution is to highlight the research methodologies in the literature and allow for comparing among them using different characteristics. The proposed taxonomy covers elementary data mining techniques such as: preprocessing, outlier detection, clustering, and classification of data. In addition, it covers centralized, distributed, offline, and online techniques from the literature.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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