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Brno University of Technology, Czech Republic

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Honeywell International, Czech Republic

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Delhi Technological University, India

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Tomas Bata University in Zlin, Czech Republic

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National Research University "MPEI", Russian Federation

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Warsaw University of Technology, Poland

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Isfahan University of Technology, Iran, Islamic Republic Of

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DIMES Department of University of Calabria, Italy

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Academy of Sciences of the Czech Republic, Czech Republic

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Czech Technical University in Prague, Czech Republic

Miroslav Voznak
VSB - Technical University of Ostrava, Czech Republic

He Wen
Hunan University, China

Otakar Wilfert
Brno University of Technology, Czech Republic


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An Evolutionary Algorithm to Mine High-Utility Itemsets

Jerry Chun-Wei Lin, Lu Yang, Philippe Fournier-Viger, Jaroslav Frnda, Lukas Sevcik, Miroslav Voznak

DOI: 10.15598/aeee.v13i4.1474


Abstract

High-utility itemset mining (HUIM) is a critical issue in recent years since it can be used to reveal the profitable products by considering both the quantity and profit factors instead of frequent itemset mining (FIM) of association rules (ARs). In this paper, an evolutionary algorithm is presented to efficiently mine high-utility itemsets (HUIs) based on the binary particle swarm optimization. A maximal pattern (MP)-tree strcutrue is further designed to solve the combinational problem in the evolution process. Substantial experiments on real-life datasets show that the proposed binary PSO-based algorithm has better results compared to the state-of-the-art GA-based algorithm.

Keywords


Binary PSO; evolutionary computation; particle swarm optimization; utility-itemset mining; tree.

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