• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>International Symposium on Symbolic and Numeric Algorithms for Scientific Computing;Workshop on Management of Resources and Services in Cloud and Sky Computing;Workshop on HPC Services;Workshop on Agents for Complex Systems >A Fraudster in a Haystack: Crafting a Classifier for Non-delivery Fraud Prediction at Online Auction Sites
【24h】

A Fraudster in a Haystack: Crafting a Classifier for Non-delivery Fraud Prediction at Online Auction Sites

机译：在大海捞针中的欺诈者：在线拍卖网站制作用于非送货欺诈预测的分类器

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Non-delivery fraud is a recurring problem at online auction sites: false sellers that list inexistent products just to receive payments and disappear, possibly repeating the swindle with another identity. The high transaction volume of these sites calls for the use of machine learning techniques in fraud prediction systems, at least for the identification of suspect sellers which deserve further expert analysis. In our work we identified a set of features related to listings, sellers and product categories, and built a system for fraud prediction taking into account the high class imbalance of real data, since fraud is a relatively rare event. The identified features are all based on publically accessible data, opening the possibility of developing fraud prediction systems independent of site operators. We tested the proposed system with data collected from a major online auction site, obtaining encouraging results on identification of fraudsters before they strike, while keeping the number of false positives low.
机译：非送货欺诈是在线拍卖网站的重复问题：虚假卖家列出不存在的产品，只需接收付款和消失，可能会与另一种身份重复诈骗。这些网站的高交易量呼吁在欺诈预测系统中使用机器学习技术，至少用于识别可疑的卖家，这些销售商应该得到进一步的专家分析。在我们的工作中，我们确定了一系列与列表，卖家和产品类别相关的功能，并建立了一个用于欺诈预测的系统，考虑到真实数据的高级失衡，因为欺诈是一个相对罕见的事件。所识别的功能全部基于公开访问数据，打开独立于站点运营商的欺诈预测系统的可能性。我们测试了从主要在线拍卖网站收集的数据的建议系统，获得令人鼓舞的结果在罢工之前识别欺诈者，同时保持误报的数量。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号