학술논문

An Efficient Parallel Association Rules Mining Algorithm for Fault Diagnosis
Document Type
Article
Source
Key Engineering Materials; May 2016, Vol. 693 Issue: 1 p1326-1330, 5p
Subject
Language
ISSN
10139826; 16629795
Abstract
With the development of Internet industry, equipment data is increasing. The traditional method is not suitable for processing large data. Aiming at inefficient problem of Apriori algorithm when mining very large database, an efficient parallel association rules mining algorithm (Advanced Pruning Parallel Apriori Algorithm) based on a cluster is presented. APPAA algorithm can enhance the mining efficiency, as well as the system’s extension. Experimental results show that APPAA algorithm cuts down 85% mining time of Apriori, and it has good characteristics of parallel and expandable.so it is suitable for mining very large size database of fault diagnosis.