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    A Fast Minimal Infrequent Itemset Mining Algorithm


    Demchuk, Kostyantyn and Leith, Douglas J. (2014) A Fast Minimal Infrequent Itemset Mining Algorithm. Working Paper. arXiv.org. (Submitted)

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    Abstract

    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: Monograph (Working Paper)
    Additional Information: Working paper submitted for publication in ACM Transactions on Knowledge Discovery from Data.
    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: 5951
    Identification Number: arXiv:1403.6985
    Depositing User: Professsor Douglas Leith
    Date Deposited: 11 Mar 2015 17:02
    Publisher: arXiv.org
    Refereed: Yes
    URI:

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