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文章基本信息

  • 标题:A Survey of Data Mining-based Fraud Detection
  • 本地全文:下载
  • 作者:R.Anitha
  • 期刊名称:International Journal of Innovative Research in Science, Engineering and Technology
  • 印刷版ISSN:2347-6710
  • 电子版ISSN:2319-8753
  • 出版年度:2016
  • 卷号:5
  • 期号:3
  • 页码:2896
  • DOI:10.15680/IJIRSET.2016.0503025
  • 出版社:S&S Publications
  • 摘要:This survey paper categories, compares, and summaries from different articles in automated frauddetection. It defines the professional fraudster, focuses the main types and subtypes of known fraud, and presents thenature of data evidence collected within affected industries. Within the business context of mining the data to achievehigher cost savings, this research presents methods and techniques together with their problems. Compared to allreviews on fraud detection, this survey covers more technical articles and is the only one, to the best of our knowledge,which proposes alternative data and solutions from related domains.
  • 关键词:Data mining applications; automated fraud detection; adversarial detection.
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