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基于评论关系图的垃圾评论者检测研究 被引量：3

Research on review spammer detection based on review graph
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摘要 提出一种基于评论关系图的产品垃圾评论者检测方法.该方法考虑了评论者、评论、商店以及回复者之间的关系,构造出四者的评论关系图,根据评论真实度获得评论者的可信度,从而检测出产品垃圾评论者.实验结果表明,与未考虑可信回复者特征的识别方法相比,本文方法的准确率提升了4%. We proposed a new method to spammer detection based on the review graph. The method captures the relationships among reviewers, reviews, stores and respondents, then we construct the review graph, and calculate the trustiness of reviewers according to honesty of reviews to identify suspicious reviewers. The experiment results show that the accuracy of this method has been improved by 4%, compared with the previous method without consideration of the respondents＇ trustiness.
作者 林秀娇 魏晶晶 刘月 廖祥文
机构地区 福州大学数学与计算机科学学院 福建省网络计算与智能信息处理重点实验室 福建江夏学院电子信息科学学院
出处 《福州大学学报（自然科学版）》 CAS 北大核心 2015年第2期170-175,共6页 Journal of Fuzhou University(Natural Science Edition)
基金 国家自然科学基金资助项目(61300105) 教育部博士点基金联合资助项目(2012351410010) 福建省高校产学合作科技重大项目(2010J05133) 福州市科技计划资助项目(2012-G-113 2013-PT-45)
关键词 垃圾评论者 评论关系图 可信回复者 review spammer review graph trustiness respondents
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献18

  • 1Jindal N, Liu B. Review spam detection[ C]//Proceedings of the 16th International Conference on World Wide Web. Banff: ACM, 2007:1 189-1 190. DOI: 10. 1145/1242572. 1242759.
  • 2Jindal N, Liu B. Analyzing and detecting review spam[ C ]//Proceeding of the 7th IEEE International Conference on Data Min- ing( ICDM07 ). Nebraska : IEEE Computer Society, 2007 : 547 - 552. DOI : 10.1109/ICDM. 2007. 68.
  • 3Jindal N, Liu B. Opinion spam and analysis [ C ]//Proceedings of the International Conference on Web Search and Web Data Mining. California: ACM, 2008: 219-230. DOI: 10. 1145/1341531. 1341560.
  • 4Lai C L, Xu K Q, Lau R Y K. et al. Toward a language modeling approach for consumer review spam detection[ C ]//Proceed- ings of the IEEE International Conference on Conference on E - Business Engineering. Shanghai : [ s. n. ]. 2010 : 1 - 8. DOI : 10. 1109/ICEBE. 2010. 47.
  • 5Lira E P, Nguyen V A, Jindal N, et al. Detecting product review spammers using rating behaviors [ C ]// Proceedings of the 19th ACM International Conference on Information and Knowledge Management. Toronto: ACM, 2010:939 -948. DOI: 10. 1145/1871437. 1871557.
  • 6邱云飞,王建坤,邵良杉,刘大有.基于用户行为的产品垃圾评论者检测研究[J].计算机工程,2012,38(11):254-257. 被引量：16
  • 7Wu G, Greene D, Smyth B, et al. Distortion as a validation criterion in the identification of suspicious reviews[ C]//Proceed- ings of the First Workshop on Social Media Analytics. Washington: ACM, 2010 : 10 - 13. DOI : 10. 1145/1964858. 1964860.
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二级参考文献48

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共引文献25

同被引文献33

引证文献3

二级引证文献11

福州大学学报（自然科学版）
2015年 第2期

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