Foundation for Frequent Pattern Mining Algorithms’ Implementation

International Journal of Computer Trends and Technology (IJCTT)          
© - July Issue 2013 by IJCTT Journal
Volume-4 Issue-7                           
Year of Publication : 2013
Authors :Prof. Paresh Tanna, Dr. Yogesh Ghodasara


Prof. Paresh Tanna, Dr. Yogesh Ghodasara"Foundation for Frequent Pattern Mining Algorithms’ Implementation"International Journal of Computer Trends and Technology (IJCTT),V4(7):2159-2163 July Issue 2013 .ISSN Published by Seventh Sense Research Group.

Abstract: - As with the development of the IT technologies, the amount of accumulated data is also increasing. Thus the role of data mining comes into picture. Association rule mining becomes one of the significant responsibilities of descriptive technique which can be defined as discovering meaningful patterns from large collection of data. The frequent pattern mining algorithms determine the frequent patterns from a database. Mining frequent itemset is very fundamental part of association rule mining. Many algorithms have been proposed from last many decades including majors are Apriori, Direct Hashing and Pruning, FP-Growth, ECLAT etc. The aim of this study is to analyze the existing techniques for mining frequent patterns and evaluate the performance of them by comparing Apriori and DHP algorithms in terms of candidate generation, database and transaction pruning. This creates a foundation to develop newer algorithm for frequent pattern mining.


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Keywords : — Association rule, Frequent pattern mining, Apriori, DHP, Foundation Implementation Study.