Open AccessDesign and Development of Apriori Algorithm for Sequential to concurrent mining using MPI
Author(s) -
Urmila R. Pol
Publication year - 2013
Publication title -
international journal of computer and technology
Language(s) - English
Resource type - Journals
ISSN - 2277-3061
DOI - 10.24297/ijct.v10i7.7026
Subject(s) - apriori algorithm , computer science , association rule learning , pace , data mining , a priori and a posteriori , big data , message passing , scale (ratio) , base (topology) , algorithm , data science , distributed computing , mathematics , philosophy , physics , geodesy , epistemology , quantum mechanics , geography , mathematical analysis
Owing to the conception of big data and massive data processing there are increasing owes related to the temporal aspects of the data processing. In order to address these issues a continuous progression in data collection, storage technologies, designing and implementing large-scale parallel algorithm for Data mining is seen to be emerging in a rapid pace. In this regards, the Apriori algorithms have a great impact for finding frequent item sets using candidate generation. This paper presents highlights on parallel algorithm for mining association rules using MPI for passing message base in the Master-Slave based structural model.