Generating associations rule mining using Apriori and FPGrowth Algorithms

  IJCOT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© - April Issue 2013 by IJCTT Journal
Volume-4 Issue-4                           
Year of Publication : 2013
Authors :J.Suresh, P.Rushyanth, Ch.Trinath

MLA

J.Suresh, P.Rushyanth, Ch.Trinath"Generating associations rule mining using Apriori and FPGrowth Algorithms"International Journal of Computer Trends and Technology (IJCTT),V4(4):887-892 April Issue 2013 .ISSN 2231-2803.www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract: -Mining frequent itemsets from the large transactional database is one of the most challenging problems in data mining. In many real world scenarios, the data is not extracted from single data source but from distributed and heterogeneous ones. The discovered knowledge is expected to better business operations. In data mining methods association rule mining is one of the most popular one. However, mining informative patterns using association rules often results in a very large no of founding patterns, leaving the analyst with the task to go through all the rules and discover interesting ones In this paper we present a generating associations rules using Apriori and FPGrowth algorithms.

 

References-

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Keywords —heterogeneous data, discovered knowledge, complex data, associations, frequent items, informative patterns.