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Modified bees swarm optimization algorithm for association rules mining
Other Title(s)
خوارزمية سرب النحل الأمثل المعدلة للتنقيب عن قواعد الارتباط
Joint Authors
Duaimi, Mahdi Kazzar
Muhammad, Rasha Abbud
al-Ubaydi, Ahmad Tariq Sadiq
Source
Issue
Vol. 58, Issue 1B (31 Mar. 2017), pp.364-376, 13 p.
Publisher
University of Baghdad College of Science
Publication Date
2017-03-31
Country of Publication
Iraq
No. of Pages
13
Main Subjects
Abstract EN
Mining association rules is a popular and well-studied method of data mining tasks whose primary aim is the discovers of the correlation among sets of items in the transactional databases.
However, generating high- quality association rules in a reasonable time from a given database has been considered as an important and challenging problem, especially with the fast increasing in database's size.
Many algorithms for association rules mining have been already proposed with promosing results.
In this paper, a new association rules mining algorithm based on Bees Swarm Optimization metaheuristic named Modified Bees Swarm Optimization for Association Rules Mining (MBSO-ARM) algorithm is proposed.
Results show that the proposed algorithm can be used as an alternative to the traditional methods.
American Psychological Association (APA)
Muhammad, Rasha Abbud& Duaimi, Mahdi Kazzar& al-Ubaydi, Ahmad Tariq Sadiq. 2017. Modified bees swarm optimization algorithm for association rules mining. Iraqi Journal of Science،Vol. 58, no. 1B, pp.364-376.
https://search.emarefa.net/detail/BIM-732201
Modern Language Association (MLA)
Duaimi, Mahdi Kazzar…[et al.]. Modified bees swarm optimization algorithm for association rules mining. Iraqi Journal of Science Vol. 58, no. 1B (2017), pp.364-376.
https://search.emarefa.net/detail/BIM-732201
American Medical Association (AMA)
Muhammad, Rasha Abbud& Duaimi, Mahdi Kazzar& al-Ubaydi, Ahmad Tariq Sadiq. Modified bees swarm optimization algorithm for association rules mining. Iraqi Journal of Science. 2017. Vol. 58, no. 1B, pp.364-376.
https://search.emarefa.net/detail/BIM-732201
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 375-376
Record ID
BIM-732201