• DocumentCode
    3363147
  • Title

    Application of Systematic Data Mining for Prediction of Biological Quality Indices

  • Author

    Bakhtina, Uliana ; Fleischer, Dirk ; Jannaschk, Kai

  • Author_Institution
    Inf. Syst. Eng., Christian-Albrechts-Univ. Kiel, Kiel, Germany
  • fYear
    2013
  • fDate
    26-30 Aug. 2013
  • Firstpage
    95
  • Lastpage
    99
  • Abstract
    Data mining is not only a simple application of an algorithm on the data set. It is rather a systematic approach that is absolutely necessary, if we want to obtain useful and meaningful patterns from data. This paper shows how the usage of systematic data mining can help to simplify the first determination of the quality of marine habitats in the western Baltic Sea. The Benthic Quality Index (BQI) has been introduced within the European Union Water Framework Directive to assess the quality of marine habitats. The index is based on sensitivity/tolerance classification and quantitative information on the composition of soft-bottom macro fauna. The calculation of the index is based on the exact designation of the found taxa.
  • Keywords
    biology computing; data mining; microorganisms; BQI; European Union water framework directive; benthic quality index; biological quality indice prediction; data set; marine habitat quality determination; quality assessment; sensitivity classification; soft-bottom macrofauna; systematic data mining; tolerance classification; western Baltic Sea; Algorithm design and analysis; Biological system modeling; Data mining; Decision trees; Europe; Indexes; BQI; classification; decision tree; splitting criterion; systematic data mining;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Database and Expert Systems Applications (DEXA), 2013 24th International Workshop on
  • Conference_Location
    Los Alamitos, CA
  • ISSN
    1529-4188
  • Print_ISBN
    978-0-7695-5070-1
  • Type

    conf

  • DOI
    10.1109/DEXA.2013.41
  • Filename
    6621353