An Efficient Approach for Accurate Frequent Pattern Mining Practising Threshold Values

Authors

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

Keywords:

Data Mining, Frequent Pattern Mining, Closed Item Sets, Close Frequent Patterns, Minimum Support Threshold

Abstract

Frequent pattern mining is the highest priority research area for researchers in data mining. It covers major real world applications. Many algorithms, techniques and tools are available for frequent pattern mining with popular Apriori and FP growth. Many algorithms have been designed to mine frequent closed item sets using single minimum support value approaches and various data structures. However, it is necessary to improve the existing methods in terms of execution time and memory consumption as well as the reduced item sets. Along with this our paper represent the new method to generate frequent closed item set. The proposed method is based on the concept of data set reduction but with preserving the interesting and important patterns. Proposed method is focused with the concept of dual minimum threshold values. The experimental results have shown that the proposed methodology is not only generating the closed item sets with reduced data set but also less mining time and memory space.

References

  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. "Data Elimination Based Technique for Mining Frequent Closed Item Set" by Kamlesh Ahuja and Sarika Jain, Year 2017, IEEE
  4. Mining Frequent Patterns with Multiple Minimum Supports using Basic Apriori" by Tiantian Xu, Xiangjun Dong, Year 2013 in Ninth International Conference on Natural Computation (ICNC)
  5. "An optimized frequent pattern mining algorithm with multiple minimum supports" by Hsiao-Wei Hu, Hao-Chen Chang, Wen-Shiu Lin, Year 2016 in IEEE International Conference on Big Data (Big Data)
  6. An Efficient Algorithm For Mining Top-Rank-K Frequent Patterns From Uncertain Databases" by Neha Goyal and S K Jain,Year 2016, IEEE
  7. An Efficient Algorithm For Mining Top-Rank-K Frequent Patterns From Uncertain Databases" by Neha Goyal and S K Jain,Year 2016, IEEE
  8. "An Improved Algorithm for Mining Frequent Inter - Transaction Patterns" by Thanh-Ngo Nguyen, Loan T.T. Nguyen, Ngoc- Thanh Nguyen, Year 2017 European Union Journals
  9. "A Review paper for mining Frequent Closed Itemsets" by Dungarval Jayesh and Neeru Yadav, Year 2014, International Journal of Advance Research in Computer Science and Management Studies Volume 2, Issue 1, January 2014 pg. 534-537
  10. "Efficient algorithms for mining erasable closed patterns from product datasets" by Tuong Le, Giang Nguyen, Tzung-Pei Hong, Year 2016 in IEEE Access Journal
  11. "An Improved and Efficient Frequent Pattern Mining Approach to Discover Frequent Patterns among Important Attributes in Large Data set Using IA-TJFGTT" by Saravanan. Suba, Dr.T. Christopher, Year 2016 in IEEE International Conference on Advances in Computer Applications (ICACA)
  12. "A Survey Paper For Finding Frequent Pattern In Text Mining", Ms. Sonam Tripathi , Asst Prof. Tripti Sharma, International Journal of Advanced Research in Computer Engineering & Technology (IJARCET) Volume 4 Issue 3, March 2015
  13. "Frequent Itemset Mining in Data Mining: A Survey", Rana Ishita, Amit Rathod, International Journal of Computer Applications (0975-8887) Volume 139
  14. "Frequent Itemset Mining Algorithms :A Literature Survey", O.Jamsheela, Raju.G,Year 2015 in IEEE Journal
  15. " Frequent Pattern Mining under Multiple Support Thresholds" by SADEQ DARRAB, BELGIN ERGENÇ in WSEAS TRANSACTIONS on COMPUTER RESEARCH, 2016
  16. "An efficient algorithm for mining maximal frequent patterns over data streams" by Junrui Yang , Yanjun Wei , Fenfen Zhou in 7th International Conference on Intelligent Human-Machine Systems and Cybernetics, 2015
  17. "Frequent Pattern Generation in AssociationRule Mining using Weighted Support"by Subrata Bose and Subrata Datta, year 2015, IEEE

Try to solve the new Formula Cube! It works exactly like a Rubik's Cube but it is only $2, from China. Learn to solve it with the tutorial on rubiksplace.com or use the solver to calculate the solution in a few steps.

International Journal of Scientific Research in Science, Engineering and Technology

Downloads

Published

2018-04-30

Issue

Volume 4, Issue 4, March-April-2018

Section

Research Articles

License

Copyright (c) IJSRSET

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Janak Thakkar, Dr. Mehul Parikh, " An Efficient Approach for Accurate Frequent Pattern Mining Practising Threshold Values, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 4, pp.1433-1436, March-April-2018.