• DocumentCode
    2106761
  • Title

    Identity attributes quantitative analysis and the development of a metrics model using text mining techniques and information theory

  • Author

    Phiri, Jackson ; Zhao, Tiejun

  • Author_Institution
    Machine Intell. & Natural Language Process. Group, Harbin Inst. of Technol., Harbin, China
  • fYear
    2010
  • fDate
    17-19 Dec. 2010
  • Firstpage
    390
  • Lastpage
    393
  • Abstract
    Term weighting has been applied to quantify and rank text data in information retrieval. Shannon´s information theory called entropy is another area that is used to quantify information. In this paper, term weighting and entropy are used to compose an identity attribute metric model. A set of application forms are used to form a sample space of identity attributes and three corpora are used to generate the required statistics used to compose an identity attribute metric model. The composed metric model has application in point based authentication systems, such as banking, immigration and implementing intelligent authentication systems.
  • Keywords
    data mining; entropy; information retrieval; Shannon information theory; entropy; identity attribute metric model; identity attribute quantitative analysis; information retrieval; point based authentication system; rank text data; term weighting; text mining technique; Authentication; Color; Entropy; Information theory; Measurement; Text mining; Entropy; Identity Attributes; Metrics; Multimode Authentication; Term Weight;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory and Information Security (ICITIS), 2010 IEEE International Conference on
  • Conference_Location
    Beijing
  • Print_ISBN
    978-1-4244-6942-0
  • Type

    conf

  • DOI
    10.1109/ICITIS.2010.5689588
  • Filename
    5689588