• Title of article

    EXPEDITE: EXPress closED ITemset Enumeration

  • Author/Authors

    Aliberti، نويسنده , , Giulio and Colantonio، نويسنده , , Alessandro and Di Pietro، نويسنده , , Roberto and Mariani، نويسنده , , Riccardo، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2015
  • Pages
    12
  • From page
    3933
  • To page
    3944
  • Abstract
    In this paper, we introduce EXPress closED ITemset Enumeration (Expedite), a new frequent closed itemset (FCI) miner designed to speed up the process of FCIs extraction from a dataset of transactions. Compared to the state of the art, Expedite provides a CPU time saving of up to two orders of magnitude without compromising other dimensions of performance (e.g. memory). The reason why it is so fast is that Expedite wastes less time in mining intermediate item sets that are discarded in later phases of the algorithm. More specifically, it cuts down the number of both duplicate FCIs—those generated multiple times by the algorithm—and infrequent itemsets—those with low support or no supporting transactions. This feature, enjoyable by both sparse and dense datasets, is analytically motivated first, and then experimentally supported by extensive tests on real datasets. As a further contribution, we propose two alternative implementations of Expedite that perform even better than the basic version, although they rely on particular features of the input dataset.
  • Keywords
    Closed itemsets , Frequent itemsets , Algorithms , DATA MINING , knowledge discovery
  • Journal title
    Expert Systems with Applications
  • Serial Year
    2015
  • Journal title
    Expert Systems with Applications
  • Record number

    2355872