PHUI-GA:GPU-based efficiency evolutionary algorithm for mining high utility itemsets

JIANG Haipeng ¹WU Guoqing ²SUN Mengdan ²LI Feng ³SUN Yunfei ⁴FANG Wei¹

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作者信息

1. Jiangsu Provincial Engineering Laboratory of Pattern Recognition and Computational Intelligence,Department of Computer Science and Technology,Jiangnan University,Wuxi 214122,China
2. China Ship Scientific Research Center,Wuxi 214082,China;Taihu Laboratory of Deepsea Technological Science,Wuxi 214082,China
3. China Ship Scientific Research Center,Wuxi 214082 China
4. Department of Mathematics,Nanjing University,Nanjing 210023,China
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Abstract

Evolutionary algorithms(EAs)have been used in high utility itemset mining(HUIM)to address the problem of discover-ing high utility itemsets(HUIs)in the exponential search space.EAs have good running and mining performance,but they still require huge computational resource and may miss many HUIs.Due to the good combination of EA and graphics processing unit(GPU),we propose a parallel genetic algorithm(GA)based on the platform of GPU for mining HUIM(PHUI-GA).The evolution steps with improvements are performed in central processing unit(CPU)and the CPU intensive steps are sent to GPU to eva-luate with multi-threaded processors.Experiments show that the mining performance of PHUI-GA outperforms the existing EAs.When mining 90％HUIs,the PHUI-GA is up to 188 times better than the existing EAs and up to 36 times better than the CPU parallel approach.

Key words

high utility itemset mining(HUIM)/graphics process-ing unit(GPU)parallel/genetic algorithm(GA)/mining perfor-mance

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基金项目

National Natural Science Foundation of China(62073155)

National Natural Science Foundation of China(62002137)

National Natural Science Foundation of China(62106088)

National Natural Science Foundation of China(62206113)

High-End Foreign Expert Recruitment Plan(G2023144007L)

Fundamental Research Funds for the Central Universities(JUSRP221028)

出版年

2024

系统工程与电子技术(英文版)

中国航天科工防御技术研究院中国宇航学会中国系统工程学会中国系统仿真学会

系统工程与电子技术(英文版)

CSTPCD

影响因子：0.64

ISSN：1004-4132

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