From fingerprint to writeprint

ABSTRACT

Identifying the key features to help identify and trace online authorship.

REFERENCES

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• 6: Huan Liu , Hiroshi Motoda, Feature Selection for Knowledge Discovery and Data Mining, Kluwer Academic Publishers, Norwell, MA, 1998
• 7: McEnery A. and Oakes, M. Authorship Studies/Textual Statistics. Marcel Dekker, 2000.
• 8: Mosteller, F. and Wallace, D.L. Inference and Disputed Authorship: The Federalist. Addison-Wesley, 1964.
• 9: Rudman, J. The state of authorship attribution studies: some problems and solutions. Computers and the Humanities 31, (1998), 351--365.
• 10: Efstathios Stamatatos , George Kokkinakis , Nikos Fakotakis, Automatic text categorization in terms of genre and author, Computational Linguistics, v.26 n.4, p.471-495, December 2000 [doi>10.1162/089120100750105920]
• 11: Yule, G.U. The Statistical Study of Literary Vocabulary. Cambridge University Press, 1944.
• 12: Rong Zheng , Jiexun Li , Hsinchun Chen , Zan Huang, A framework for authorship identification of online messages: Writing-style features and classification techniques, Journal of the American Society for Information Science and Technology, v.57 n.3, p.378-393, February 2006 [doi>10.1002/asi.v57:3]

INDEX TERMS

Primary Classification:
  K. Computing Milieux
  K.4 COMPUTERS AND SOCIETY
      K.4.1 Public Policy Issues
          Subjects: Abuse and crime involving computers

Additional Classification:
  K. Computing Milieux
  K.4 COMPUTERS AND SOCIETY
      K.4.2 Social Issues
  K.6 MANAGEMENT OF COMPUTING AND INFORMATION SYSTEMS
      K.6.5 Security and Protection (D.4.6, K.4.2)

General Terms:
Security