Efficient hiding of confidential high-utility itemsets with minimal side effects

Privacy preserving data mining (PPDM) is an emerging research problem that has become critical in the last decades. PPDM consists of hiding sensitive information to ensure that it cannot be discovered by data mining algorithms. Several PPDM algorithms have been developed. Most of them are designed f...

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Veröffentlicht in:	Journal of experimental & theoretical artificial intelligence 2017-11, Vol.29 (6), p.1225-1245
Hauptverfasser:	Lin, Jerry Chun-Wei, Hong, Tzung-Pei, Fournier-Viger, Philippe, Liu, Qiankun, Wong, Jia-Wei, Zhan, Justin
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Data mining Deletion Evolutionary algorithms Fitness Genetic algorithm Genetic algorithms high-utility mining Integrity privacy preserving data mining Side effects Simulation transaction deletion
Online-Zugang:	Volltext
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