CCE Theses and Dissertations
Date of Award
2009
Document Type
Dissertation
Degree Name
Doctor of Information Science
Department
Graduate School of Computer and Information Sciences
Advisor
Junping Sun
Committee Member
Michael Laszlo
Committee Member
James Cannady
Keywords
Apriori, Association rules, Data mining, Distributed algorithms, Lattice, Parallel systems
Abstract
The discovery of interesting patterns from database transactions is one of the major problems in knowledge discovery in database. One such interesting pattern is the association rules extracted from these transactions. Parallel algorithms are required for the mining of association rules due to the very large databases used to store the transactions. In this paper we present a parallel algorithm for the mining of association rules. We implemented a parallel algorithm that used a lattice approach for mining association rules. The Dynamic Distributed Rule Mining (DDRM) is a lattice-based algorithm that partitions the lattice into sublattices to be assigned to processors for processing and identification of frequent itemsets. Experimental results show that DDRM utilizes the processors efficiently and performed better than the prefix-based and partition algorithms that use a static approach to assign classes to the processors. The DDRM algorithm scales well and shows good speedup.
NSUWorks Citation
Wessel Morant Thomas. 2009. Parallel Mining of Association Rules Using a Lattice Based Approach. Doctoral dissertation. Nova Southeastern University. Retrieved from NSUWorks, Graduate School of Computer and Information Sciences. (361)
https://nsuworks.nova.edu/gscis_etd/361.