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Erschienen in:
2010 | OriginalPaper | Buchkapitel
BBA Algorithm
verfasst von : Aris Gkoulalas-Divanis, Vassilios S. Verykios
Erschienen in: Association Rule Hiding for Data Mining
Verlag: Springer US
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Sun & Yu [66, 67] in 2005 proposed the first frequent itemset hiding methodology that relies on the notion of the
border
[46] of the nonsensitive frequent itemsets to track the impact of altering transactions in the original database. By evaluating the impact of each candidate item modification to the itemsets of the revised positive border, the algorithm greedily selects to apply those modifications (item deletions) that cause the least impact to the border itemsets. As already covered in the previous chapter, the border itemsets implicitly dictate the status (i.e., frequent vs. infrequent) of every itemset in the database. Consequently, the quality of the borders directly affects the quality of the sanitized database that is produced by the hiding algorithm.