A Novel Incremental Algorithm for Frequent Itemsets Mining in Dynamic Datasets

  • Raudel Hernández-León
  • José Hernández-Palancar
  • J. A. Carrasco-Ochoa
  • J. Fco. Martínez-Trinidad
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5197)


Frequent Itemsets (FI) Mining is one of the most researched areas of data mining. When some new transactions are appended, deleted or modified in a dataset, updating FI is a nontrivial task since such updates may invalidate existing FI or introduce new ones. In this paper a novel algorithm suitable for FI mining in dynamic datasets named Incremental Compressed Arrays is presented. In the experiments, our algorithm was compared against some algorithms as Eclat, PatriciaMine and FP-growth when new transactions are added or deleted.


Data mining Frequent itemsets Dynamic datasets 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Raudel Hernández-León
    • 1
    • 2
  • José Hernández-Palancar
    • 1
  • J. A. Carrasco-Ochoa
    • 2
  • J. Fco. Martínez-Trinidad
    • 2
  1. 1.Advanced Technologies Application Center (CENATAV)La HabanaCuba
  2. 2.Computer Science Department National Institute of AstrophysicsOptics and ElectronicsPueblaMexico

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