A survey of incremental high‐utility itemset mining

Traditional association rule mining has been widely studied. But it is unsuitable for real‐world applications where factors such as unit profits of items and purchase quantities must be considered. High‐utility itemset mining (HUIM) is designed to find highly profitable patterns by considering both...

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Veröffentlicht in:	Wiley interdisciplinary reviews. Data mining and knowledge discovery 2018-03, Vol.8 (2), p.e1242-n/a
Hauptverfasser:	Gan, Wensheng, Lin, Jerry Chun‐Wei, Fournier‐Viger, Philippe, Chao, Han‐Chieh, Hong, Tzung‐Pei, Fujita, Hamido
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Data mining Decision analysis Decision making dynamic database high utility incremental mining Knowledge representation quantities Software development tools
Online-Zugang:	Volltext
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