Generate Frequent Item Sets with Modified Top down Apriori Algorithm using Mapreduce
Author(s) -
Jyoti Yadav,
Neha Sehta
Publication year - 2018
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2018916453
Subject(s) - computer science , apriori algorithm , a priori and a posteriori , data mining , algorithm , association rule learning , philosophy , epistemology
As with the advancement of the IT technologies, the data is increasing day by day and it is difficult to manage the data and find out relevant information from it. There are many conventional data mining techniques present for generating frequent item sets. Association rule mining is one of the important task of descriptive technique . Apriori algorithm is the versatile algorithm for generating frequent item sets. Challenge is to improve efficiency by taking less time and produce better results. Hadoop Map reduce introduced by Google overcomes the problem of multiple re-execution of tasks.In this paper Hybrid approach of modified apriori with Hadoop MapReduce is proposed. General Terms Modified Algorithm, Frequent Item sets,Apriori Algorithm
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