A risk detection system of e-commerce: researches based on soft information extracted by affective computing web texts

被引：0
作者：
Anzhong Huang
机构：
[1] Jiangsu Normal University,The Belt And Road Institute
来源：
Electronic Commerce Research | 2018年 / 18卷
关键词：
E-commerce; Soft information; Outlier detection; Affective computing;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
The product comments in e-commerce circumstance has a strong guidance role on customers, therefore the merchants will usually falsify bogus comments to defraud customers. In order to monitor such behaviors of merchants, we transform the comments of the same product from different merchants to eigenvector by the way of affective computing, then compare it with the vector derived from the comments on the third-party professional assessment and test websites as well as on the microblog, and identify those vectors with big deviation degree, that means the product of those merchants are possibly in fraudulence. Experiment proves that the system can recognize fraudulent merchants.
引用
收藏
页码：143 / 157
页数：14
相关论文
共 25 条
  • [1] Cen W(2009)The impacts of factors of merchants on the consumer behaviors in C2C Modern Business Trade Industry 21 112-114
  • [2] Kumar R(2005)Virtualization for manufacturing web services: A WS-RF approach International Journal of Information Technology 11 40-51
  • [3] Yan Z(2002)The value of seller trustworthiness in C2C online markets Communications of the ACM 45 45-49
  • [4] Zhang J(2004)Modeling reputation management system on online C2C market Computational & Mathematical Organization Theory 10 165-178
  • [5] Strader TJ(2007)Researches on web-service encapsulation of networked manufacturing resources: Based on WSRF Computer Engineering and Applications 43 22-25
  • [6] Ramaswami SN(2012)A detection method of Chinese microblog news topic Computer Science 39 138-141
  • [7] Yamamoto H(2004)Mining opinion features in customer reviews AAAI 4 755-760
  • [8] Ishida K(2010)Mining the chrematistics of products and affective tendencies of consumer comments on Chinese websites Application Research of Computers 27 3016-3019
  • [9] Ohta T(2010)Designing the distributed collaborative system for complex product Journal of Central South University (Science and Technology) 41 539-546
  • [10] Haojin J(2005)An effective and efficient algorithm for high dimensional outlier detection The VLDB Journal 14 211-221
123