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    A Fast Minimal Infrequent Itemset Mining Algorithm

    Demchuk, Kostiantyn (2014) A Fast Minimal Infrequent Itemset Mining Algorithm. Masters thesis, National University of Ireland Maynooth.

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    A novel fast algorithm for finding quasi identifiers in large datasets is presented. Performance measurements on a broad range of datasets demonstrate substantial reductions in run-time relative to the state of the art and the scalability of the algorithm to realistically-sized datasets up to several million records.

    Item Type: Thesis (Masters)
    Keywords: itemset mining; breadth-first algorithm; frequency-based analysis; k-anonymity; performance; load balancing;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 6325
    Depositing User: IR eTheses
    Date Deposited: 04 Sep 2015 09:54
    Funders: Science Foundation Ireland under Grant No. 11/PI/1177
      Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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