• DocumentCode
    2033404
  • Title

    Fuzzy methods for forensic data analysis

  • Author

    Stoffel, Kilian ; Cotofrei, Paul ; Han, Dong

  • Author_Institution
    Inf. Manage. Inst., Univ. of Neuchatel, Neuchâtel, Switzerland
  • fYear
    2010
  • fDate
    7-10 Dec. 2010
  • Firstpage
    23
  • Lastpage
    28
  • Abstract
    In this paper we describe a methodology and an automatic procedure for inferring accurate and easily understandable expert-system-like rules from forensic data. This methodology is based on the fuzzy set theory. The algorithms we used are described in detail, and were tested on forensic data sets. We also present in detail some examples, which are representative for the obtained results.
  • Keywords
    data analysis; fuzzy set theory; inference mechanisms; security of data; expert-system-like rules; forensic data analysis; fuzzy clustering; fuzzy inference system; fuzzy methods; fuzzy set theory; Cities and towns; Clustering algorithms; Computational intelligence; Data models; Databases; Forensics; Fuzzy sets; computational intelligence; forensic data; fuzzy clustering; fuzzy inference system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Soft Computing and Pattern Recognition (SoCPaR), 2010 International Conference of
  • Conference_Location
    Paris
  • Print_ISBN
    978-1-4244-7897-2
  • Type

    conf

  • DOI
    10.1109/SOCPAR.2010.5685848
  • Filename
    5685848
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2033404