大型数据库中考虑负项目值的高效用项目集排序策略估计

IF 0.6 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
R. Agarwal
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引用次数: 1

摘要

具有负项值的效用挖掘由于其实用性,最近在数据挖掘领域引起了人们的兴趣。以前,实用工具项集的值被认为是正的。然而,在实际应用程序中,项集可能与负的项值相关。提出了一种利用高效用项集和负效用项集重新设计订货策略的方法。首先,利用效用挖掘算法寻找高效用项集。然后,在考虑缺陷和非缺陷的情况下,估计了高效用物品的订购策略。最后通过数值算例验证了计算结果
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ordering Policy Estimation for High Utility Item-Sets Considering Negative Item Values in Large Databases
Utility mining with negative item values has recently received interest in the data mining field due to its practical considerations. Previously, the values of utility item-sets have been taken into consideration as positive. However, in real-world applications an item-set may be related to negative item values. This paper presents a method for redesigning the ordering policy by including high utility item-sets with negative items. Initially, utility mining algorithm is used to find high utility item-sets. Then, ordering policy is estimated for high utility items considering defective and non-defective items. A numerical example is illustrated to validate the results
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来源期刊
International Journal of Decision Support System Technology
International Journal of Decision Support System Technology COMPUTER SCIENCE, INFORMATION SYSTEMS-
CiteScore
2.20
自引率
18.20%
发文量
40
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