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Techniques And Algorithms Used For Knowledge Extraction From Large Volumes Of Data

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  • Ana-Maria Ramona Stancu

    ()

  • Mihaela Mocanu

    ()

Abstract

Large volumes of data have raised the problem of their use from the exploitation up to the result, and the Data Mining technology uses complex search methods that aim to identify some patterns and clusters of data, some trends in the consumers’ behavior that can be used to anticipate their future behavior. Methods for knowledge extraction from data represent classes of problems that are subject to different solving algorithms. Of all algorithms, the current paper is dealing with decision trees and we will present a classifying application on which we will study the decision trees.

Suggested Citation

  • Ana-Maria Ramona Stancu & Mihaela Mocanu, 2016. "Techniques And Algorithms Used For Knowledge Extraction From Large Volumes Of Data," Knowledge Horizons - Economics, Faculty of Finance, Banking and Accountancy Bucharest,"Dimitrie Cantemir" Christian University Bucharest, vol. 8(4), pages 44-47, December.
  • Handle: RePEc:khe:journl:v:8:y:2016:i:4:p:44-47
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    File URL: http://orizonturi.ucdc.ro/arhiva/khe-vol8-nr4-2016/7.%20TECHNIQUES%20AND%20ALGORITHMS%20USED%20FOR%20KNOWLEDGE%20EXTRACTION%20FROM%20LARGE%20VOLUMES%20OF%20DATA.pdf
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    More about this item

    Keywords

    Algorithm; Tree; Model; Rules; Techniquesjournal: Knowledge Horizons - Economics;

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

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