Ordering Policy Estimation for High Utility Item-Sets Considering Negative Item Values in Large Databases

IF 0.6 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS International Journal of Decision Support System Technology Pub Date : 2022-01-01 DOI:10.4018/ijdsst.286682
R. Agarwal
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引用次数: 1

Abstract

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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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
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
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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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