• DocumentCode
    3265708
  • Title

    Optimization of knowledge discovery process using domain knowledge

  • Author

    Owrang, M. Mehdi

  • Author_Institution
    Dept. of Comput. Sci. & Inf. Syst., American Univ., Washington, DC, USA
  • fYear
    35765
  • fDate
    8-10 Dec1997
  • Firstpage
    428
  • Lastpage
    433
  • Abstract
    Modern database technologies process large volumes of data to discover new knowledge. Some large databases make discovery computationally expensive. Additional knowledge, known as domain or background knowledge, can often guide and restrict the search for interesting knowledge. We discuss mechanisms by which domain knowledge can be used effectively in discovering knowledge from databases. In particular, we look at the use of domain knowledge to reduce the search as well as to optimize the hypotheses which represent the interesting knowledge to be discovered
  • Keywords
    database theory; deductive databases; knowledge acquisition; optimisation; search problems; very large databases; background knowledge; computationally expensive; deductive database; domain knowledge; knowledge discovery; knowledge discovery process optimization; large data volumes; large databases; search; Computer science; Data analysis; Data mining; Databases; Information systems; Packaging; Pattern recognition; Quality control; Rough sets; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Systems, 1997. IIS '97. Proceedings
  • Conference_Location
    Grand Bahama Island
  • Print_ISBN
    0-8186-8218-3
  • Type

    conf

  • DOI
    10.1109/IIS.1997.645328
  • Filename
    645328