EFIM: a fast and memory efficient algorithm for high-utility itemset mining

In recent years, high-utility itemset mining has emerged as an important data mining task. However, it remains computationally expensive both in terms of runtime and memory consumption. It is thus an important challenge to design more efficient algorithms for this task. In this paper, we address thi...

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Veröffentlicht in:	Knowledge and information systems Jg. 51; H. 2; S. 595 - 625
Hauptverfasser:	Zida, Souleymane, Fournier-Viger, Philippe, Lin, Jerry Chun-Wei, Wu, Cheng-Wei, Tseng, Vincent S.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Springer London 01.05.2017 Springer Nature B.V
Schlagworte:	Algorithms Computer memory Computer Science Consumption Data mining Data Mining and Knowledge Discovery Database Management Datasets Information Storage and Retrieval Information systems Information Systems and Communication Service Information Systems Applications (incl.Internet) IT in Business Merging Projection Regular Paper Studies Utilities Fast Utility Counting, High-utility database merging and projection Pattern mining Itemset mining, High-utility mining
ISSN:	0219-1377, 0219-3116
Online-Zugang:	Volltext
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