A Literature Survey on Association Rule Mining Algorithms

Pinar Yazgana, Ali Osman Kusakci


With the development of database technology, the need for data mining arises. As a result, Association Rule Mining(ARM) has become a very hot topic in data mining. This paper presents definition and application areas of association rules. Furthermore, a comprehensive literature review on the existing algorithms of ARM is conducted with a special focus on the performance and application areas of the algorithms. These algorithms are in general classified into three main classes: (1) based on frequent itemset, (2) based on sequential pattern, and (3) based on structured pattern. The algorithms are developed to improve the accuracy and decrease the complexity, and execution time. However, it is hard to say that they do always succeed to optimize all these aspects simultaneously. Hence, there is still some space to develop more efficient algorithms for different data structures.


Information technology; market basket analysis; association rule mining; data mining

Full Text:


DOI: http://dx.doi.org/10.21533/scjournal.v5i1.102


  • There are currently no refbacks.

Copyright (c) 2016 Pinar Yazgana, Ali Osman Kusakci

ISSN 2233 -1859

Digital Object Identifier DOI: 10.21533/scjournal

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License