Challenges to find Association Rules over various types of data items: a Survey

被引：0

作者：

Reddy, P. Amaranatha ^{[1
]}

Prasad, M. H. M. Krishna ^{[2
]}

机构：

[1] VIGNANS Univ, Dept Comp Sci & Engn, Vadlamudi 522213, AP, India

[2] JNTU, Univ Coll Engn, Dept Comp Sci & Engn, Kakinada 533003, AP, India

来源：

2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND AUTOMATION (ICCCA) | 2017年

关键词：

Data Mining; Association Rule Mining; Frequent Patteern Mining;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Association Rule Mining is a Data Mining technique used to uncover the hidden interesting relationships between item-sets in a large database. Many algorithms have been proposed to find association rules in various fields. In General, values associated with data items need not be the same type in all the databases. Applying a single algorithm for all the types of data items may not feasible. To solve this problem applying an individual algorithm for each type of data is one solution and conversion of data item values to algorithm compatible type is another solution. This paper presents basic ways of finding association rules for various kinds of data items and challenges involved in it.

引用

页码：180 / 184

页数：5

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