期刊文献+

基于机器学习的域名信用评价方法 被引量:1

Evaluation method of domain name credit based on machine learning
下载PDF
导出
摘要 针对域名自身的特点和应用特点,建立一种基于机器学习的域名信用评价自动化方法并进行实验分析。实验结果表明,该方法具有较好的正确率,符合人们的一般认识,其评价结果可以作为域名诚信管理体系的参考依据。 This paper created an automatic method,based on machine learning,to evaluate credit of domain names of their own characteristics and application features,and then made experimental analysis.As the experiment shows,the method can reach a good precision and its' results can be used as a reference of domain integrity and credit management system.
出处 《计算机应用研究》 CSCD 北大核心 2012年第2期690-692,697,共4页 Application Research of Computers
基金 国家自然科学基金资助项目(61005029)
关键词 不良应用 失信 域名 信用评价 机器学习 bad applications lack of credit domain name credit evaluation machine learning
  • 相关文献

参考文献13

  • 1MBAlib. Credit rating[ EB/OL]. (2011-02-28) [2011-03-20]. http ://wiki. mbalib, eom/wiki/Credit_Rating.
  • 2GENG Guang-gang, JIN Xiao-bo, ZHANG De-xian. Evaluating Web content quality via muhi-scale features [ C]//Proc of ECML/PKDD 2010 Discovery Challenge. 2010.
  • 3ERDELYI M, GARZO A, BENCZUR A A. Web spam classification: a few features worth more [ C ]//Proc of the 2011 Joint WICOW/AIR- Web Workshop on Web Quality. [S. 1. ] :ACM Press, 2011.
  • 4DAVIS R H, EDELMAN D B, GAMMERMAN A J. Machine-lear- ning algorithm for credit-card applications [ J]. IMA d Management Math, 1992 ,g ( 1 ) :43-51.
  • 5VIEDMA H E, PASI G, PORCEL C, et al. Evaluating the informa- tion quality of Web sites: a methodology based on fuzzy computing with words[J]. Journal of the American Society for Information Science and Technology,2006,57(4) :538-549.
  • 6ECML/PKDD. Rules : ECML/PKDD 2010 discovery challenge [ EB/ OL]. (2010- 06- 25 ) [ 2011- 03- 28 ]. http://datamining, sztaki.hu/? q = en/DiscoveryChallenge/rules.
  • 7PAGE L, BRIN S, MOTWANI R, et al. The PageRank citation ranking: bring order to the Web, Technical Report SIDL-WP- 1999- 0120[ R]. [ S. 1. ] :Stanford InfoLab,Stanford University,1999.
  • 8QUINLAN J R. CA. 5: programs for machine learning[ M]. San Ma- teo : Morgan Kaufmann Publishers, 1993.
  • 9BREIMAN L. Bagging predictors [ J ]. Machine Learning, 1996,24 (2) :123-140.
  • 10KEARNS M, VALIANT L G. Learning boolean formulae or factoring, Technical Report TR-1488[R]. Cambridge, MA:Aiken Computation Laboratory, Harvard University, 1988.

同被引文献79

引证文献1

二级引证文献10

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部