A Survey On Efficient Frequent Pattern Mining Techniques

Authors(2) :-Janak Thakkar, Dr. Mehul Parikh

Data Mining is the technique to abstract the useful data from the large dataset for different perspectives. Frequent pattern mining has become an important data mining technique to find the frequent patterns from the data set that appears frequently. Frequent Pattern Technique is widely used in financial, retail, telecommunication and many more. The major concern of these industries is faster processing of a very large amount of data. Various techniques and algorithms have been proposed for this purpose. Apriori, FP-tree are the pioneer techniques among them. In this paper, we have analysed algorithms for finding frequent patterns with the purpose of discovering how these algorithms can be used to obtain frequent patterns over large transactional databases with most efficient way in various aspects. This has been presented in the form of a comparative study of the following algorithms: Apriori, Frequent Pattern (FP) Growth, dNC-ECPM Algorithm, OCFP–growth, IA-TJ-FGTT(Important Attributes -Transaction Joining - Frequency Gathering Table Technique).

Authors and Affiliations

Janak Thakkar
IT Department, R C Technical Institute, Ahmedabad, Gujarat, India
Dr. Mehul Parikh
Associate Professor, IT Department, LDCE, Ahmedabad, Gujarat, India

Data Mining, Frequent Pattern Mining, Apriori, FP-Growth, Erasable Patterns, Close Patterns

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Publication Details

Published in : Volume 4 | Issue 2 | January-February 2018
Date of Publication : 2018-01-20
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 78-80
Manuscript Number : IJSRSET184214
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Janak Thakkar, Dr. Mehul Parikh, " A Survey On Efficient Frequent Pattern Mining Techniques , International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 2, pp.78-80, January-February-2018.
Journal URL : http://ijsrset.com/IJSRSET184214

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