Method for Mining Frequent Item Sets Considering Average Utility

被引：6

作者：

Agarwal, Reshu ^{[1
]}

Gautam, Arti ^{[2
]}

Saksena, Ayush Kumar ^{[2
]}

Rai, Amrita ^{[2
]}

Karatangi, Shylaja VinayKumar ^{[2
]}

机构：

[1] Amity Univ, Amity Inst Informat Technol, Noida, India

[2] GL Bajaj Inst Technol & Management, Greater Noida, India

来源：

2021 INTERNATIONAL CONFERENCE ON EMERGING SMART COMPUTING AND INFORMATICS (ESCI) | 2021年

关键词：

Association rule mining; Data Mining; Average Utility; Frequent Item-sets; Two-phase Mining;

D O I：

10.1109/ESCI50559.2021.9396947

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Data mining is used to determine helpful data and information from large data bases for decision making in different fields. In today's scenario, mining high-utility item-sets (HUIs) has become a current investigation area. In traditional method HUIs are found on the basis individual utility of an item-set, which in turn is calculated as the totality of the utilities of individual items. But the problem is that the above way of finding HUIs does not consider length of item-set into consideration, while calculating HUIs. In real world situations, it is desirable to calculate average utility while considering both the length of item-sets and their utilities. This paper proposes an algorithm to find the high average-utility item-sets (HAUIs) seeing both parameters i.e. length of item-sets and their utilities. A numerical example is devised to explain the proposed approach. Experiments on real life databases shows that suggested model can proficiently discover the total set of HAUIs.

引用

页码：275 / 278

页数：4

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