A Hybrid Technique for Data Mining on Balance-Sheet Data

  • G. Dattilo
  • S. Greco
  • E. Masciari
  • L. Pontieri
Conference paper

DOI: 10.1007/3-540-44466-1_42

Volume 1874 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Dattilo G., Greco S., Masciari E., Pontieri L. (2000) A Hybrid Technique for Data Mining on Balance-Sheet Data. In: Kambayashi Y., Mohania M., Tjoa A.M. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2000. Lecture Notes in Computer Science, vol 1874. Springer, Berlin, Heidelberg

Abstract

Recent rapid growth in the ability to generate and store data by more powerful Database Management Systems and hardware architecture, leads to a question: how can we take advantage of this large amount of information? Traditional methods for querying and reporting are inadequate because they can only manipulate data and the information content derived is very low. Obtaining new relationships among data and new hypotheses about them is the aim of Knowledge Discovery in Databases (KDD) which makes use of Data Mining techniques. These techniques have interesting applications for business data such as market basket analysis, financial resource planning, fraud detection and the scheduling of production processes. In this work we consider the application of Data Mining techniques for the analysis of the balance-sheets of Italian companies.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • G. Dattilo
    • 2
  • S. Greco
    • 1
    • 2
  • E. Masciari
    • 1
    • 2
  • L. Pontieri
    • 1
    • 2
  1. 1.DEIS, Univ. della CalabriaRendeItaly
  2. 2.ISI-CNRRendeItaly