山东大学学报 (工学版) ›› 2022, Vol. 52 ›› Issue (4): 118-130.doi: 10.6040/j.issn.1672-3961.0.2021.302
• • 上一篇
张春砚,韩萌*,孙蕊,杜诗语,申明尧
ZHANG Chunyan, HAN Meng*, SUN Rui, DU Shiyu, SHEN Mingyao
摘要： 为减少构建效用列表的数量和占用的内存,在时间和空间方面提高挖掘性能,提出增量闭合高效用挖掘算法(incremental closed high utility mining, ICHUM),从增量数据集中有效地挖掘闭合高效用项集。此算法提出一个增量分区效用列表结构,该结构仅通过一次数据库扫描即可构建和更新列表,更有效地处理增量数据。在构造此列表结构的过程中,算法还应用有效的融合修剪策略,从而减少无效列表的构建数量。在各种数据集上的试验结果表明,与对比算法相比,该算法减少了30%的运行时间和33%的内存消耗,具有一定的可扩展性。
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