IJSRSET calls volunteers interested to contribute towards the scientific development in the field of Science, Engineering and Technology

Home > IJSRSET184214                                                     


A Survey On Efficient Frequent Pattern Mining Techniques

Authors(2):

Janak Thakkar, Dr. Mehul Parikh
  • Abstract
  • Authors
  • Keywords
  • References
  • Details
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).

Janak Thakkar, Dr. Mehul Parikh

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

  1. First Agrawal R, Imielinski T, Swami A. Mining association rules between sets of items in large databases. In Proceedings of the 1993 ACMSIGMOD international conference on management of data(SIGMOD’93), pages207-216.1993
  2. Agrawal R, Srikant R. Fast algorithms for mining association rules. InProceedings of the 1994 international conference on very large databases(VLDB’94), pages487–499.1994
  3. Han J, Pei J, Yin Y. Mining frequent patterns without candidate generation. In Proceeding of the 2000 ACM-SIGMOD international conference on management of data (SIGMOD’00) pages1–12.2000
  4. Efficient algorithms for mining erasable closed patterns from product datasets” 10.1109/ACCESS.2017.2676803, IEEE Access
  5. “An optimized frequent pattern mining algorithm with multiple minimum supports” 2016 IEEE International Conference on Big Data (Big Data) Hsiao-Wei Hu, Hao-Chen Chang, Wen-Shiu Lin
  6. Saravanan. Suba, Dr.T. Christopher. "An Improved and Efficient Frequent Pattern Mining Approach to Discover Frequent Patterns among Important Attributes in  Large Data set Using IA-TJFGTT” 2016 IEEE International Conference on Advances in Computer Applications (ICACA)
  7. Goswami.D, Chaturvedi.A, Raghuvanshi.C “An Algorithm for Frequent Pattern Mining Based On Apriori” IJCSE 2010.
  8. Mabroukeh.N and Ezeife.C “A Taxonomy of Sequential Pattern Mining Algorithms” ACM Computing Surveys, Vol. 43, No. 1, Article 3, Publication date, November 2010

Publication Details

Published in : Volume 4 | Issue 2 | January-February - 2018
Date of Publication Print ISSN Online ISSN
2018-01-20 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
78-80 IJSRSET184214   Technoscience Academy

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.
URL : http://ijsrset.com/IJSRSET184214.php

IJSRSET Xplore

Search Your Article

Enter ID [Ex. IJSRSET14XXX]

Subscribe