• DocumentCode
    2993417
  • Title

    Efficient e-Discovery Process Utilizing Combination Method of Machine Learning Algorithms

  • Author

    Lee, Tae Rim ; Goo, Bon Min ; Kim, Hun ; Shin, Sang Uk

  • Author_Institution
    Dept. of Inf. Security the Grad. Sch., Pukyoung Nat. Univ., Busan, South Korea
  • fYear
    2011
  • fDate
    3-4 Dec. 2011
  • Firstpage
    1109
  • Lastpage
    1113
  • Abstract
    According to the widespread of digital devices and Internet, the use of electronic document is rapidly increasing in our daily life. In this situation, e-Discovery was introduced by FRCP amendments of U.S. on December 1 2006. As a result, litigants have a responsibility to produce evidences when the lawsuit is expected. To deal with this, a lot of technologies and solutions have been developed actively but there are some problems from the aspect of time and cost. So in this paper, we suggest a combination method between machine learning algorithms for an effective ESI management and the searching of evidences related to the litigation issues. Also, we analyze its expected advantages.
  • Keywords
    Internet; document handling; learning (artificial intelligence); legislation; ESI management; FRCP amendments; Internet; combination method; digital devices; e-Discovery; e-discovery process; electronic document; lawsuit; litigants; litigation issues; machine learning algorithms; Clustering methods; Information management; Law; Learning systems; Machine learning; Training; Vectors; ESI Management; Electornic Discovery; Machine Learning; e-Discovery;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Security (CIS), 2011 Seventh International Conference on
  • Conference_Location
    Hainan
  • Print_ISBN
    978-1-4577-2008-6
  • Type

    conf

  • DOI
    10.1109/CIS.2011.246
  • Filename
    6128432