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Reseach Article

A Collaborative Approach of Frequent Item Set Mining: A Survey

by Arpan Shah, Pratik Patel
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 107 - Number 8
Year of Publication: 2014
Authors: Arpan Shah, Pratik Patel
10.5120/18775-0088

Arpan Shah, Pratik Patel . A Collaborative Approach of Frequent Item Set Mining: A Survey. International Journal of Computer Applications. 107, 8 ( December 2014), 34-36. DOI=10.5120/18775-0088

@article{ 10.5120/18775-0088,
author = { Arpan Shah, Pratik Patel },
title = { A Collaborative Approach of Frequent Item Set Mining: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 107 },
number = { 8 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 34-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume107/number8/18775-0088/ },
doi = { 10.5120/18775-0088 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:40:34.169896+05:30
%A Arpan Shah
%A Pratik Patel
%T A Collaborative Approach of Frequent Item Set Mining: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 107
%N 8
%P 34-36
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Data mining defines hidden pattern in data sets and association between the patterns. In data mining, association rule mining is key technique for discovering useful patterns from large collection of data. Frequent iemset mining is a step of association rule mining. Frequent itemset mining is used to gather itemsets after discovering association rules. In this paper, we have explained fundamentals of frequent itemset mining. We have defined present's techniques for frequent item set mining. From the large variety of capable algorithms that have been established we will compare the most important ones. We will organize the algorithms and investigate their run time performance.

References
  1. S. Neelima, N. Satyanarayana and P. Krishna Murthy3,"A Survey on Approaches for Mining Frequent Itemsets", IOSR Journal of Computer Engineering (IOSR-JCE) e-ISSN: 2278-0661, p-ISSN: 2278-87
  2. Aakansha Saxena, Sohil Gadhiya , "A Survey on Frequent Pattern Mining Methods Apriori, Eclat, FP growth", 2014 IJEDR | Volume 2, Issue 1 | ISSN: 2321-9932.
  3. Bharat Gupta, Dr. Deepak Garg, "FP-Tree Based Algorithms Analysis: FP Growth, COFI-Tree and CT-PRO", International Journal on Computer Science and Engineering (IJCSE) 2013
  4. Wei Zhang, Hongzhi Liao. Na Zhao, "Research on the FP Growth Algorithm about Association Rule Mining", 2008 International Seminar on Business and Information Management
  5. SakthiNathiarasan1, Kalaiyarasi2, Manikandan3, Literature Review on Infrequent Itemset Mining Algorithm, International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, Issue 8, August 2014.
  6. Varsha Mashoria, Anju Singh, "Literature Survey on Various Frequent Pattern Mining Algorithm", IOSR Journal of Engineering (IOSRJEN) e-ISSN: 2250-3021, p-ISSN: 2278-8719 Vol. 3, Issue 1 (Jan. 2013), ||V1|| PP 58-64
  7. Vikas Kumar, Sangita Satapathy, "A Review on Algorithms for Mining Frequent Itemset Over Data Stream", Volume 3, Issue 4, April 2013 ISSN: 2277 128X
  8. Pradeep Rupayla, Kamlesh Patidar, "A Comprehensive Survey of Frequent Item Set mining Methods", IJETAE, ISSN 2250-2459, ISO 9001:2008 Certified Journal, Volume 4, Issue 4, April 2014)
  9. Neelesh Kumar Kori, Ramratan Ahirwal, Dr. Yogendra Kumar Jain, "Efficient Frequent Itemset Mining Mechanism Using Support Count", International Journal of Application or Innovation in Engineering & Management (IJAIEM), Volume 1, Issue 1, September 2012
  10. Shipra Khare , Prof. Vivek Jain, "A Review on Infrequent Weighted Itemset Mining using Frequent Pattern Growth", (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (2) , 2014, 1642-1647
  11. Le Wang, Lin Feng Jing Zhang, Pengyu Liao, "An Efficient Algorithm of Frequent Itemsets Mining Based on MapReduce", Journal of Information & Computational Science 11:8 (2014) 2809–2816 May 20, 2014
  12. S. Vijay Jeetesh Kumar Jain, Nirupama Tiwari, Manoj Ramaiya, "A Survey: on Association Rule Mining", International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 1, January –February 2013, pp. 2065-2069
  13. S. Vijayaranii el. al. "Mining Frequent Item Sets over Data Streams using Éclat Algorithm" International Conference on Research Trends in Computer Technologies (ICRTCT-2013).
  14. Jian Pei , Jiawei Han , Hongjun Lu , Shojiro Nishio , Shiwei Tang , Dongqing Yang "H-Mine: Hyper-Structure Mining of Frequent Patterns in Large Databases".
  15. H. Altay Güvenir, "An Algorithm for Mining Association Rules Using Perfect Hashing and Database Pruning's
  16. T. Karthikeyan1 and N. Ravikumar, "A Survey on Association Rule Mining"International Journal of Advanced Research in Computer and Communication Engineering Vol. 3, Issue 1, January 2014.
  17. Jeetesh Kumar Jain, Nirupama Tiwari, Manoj Ramaiya, "A Survey: on Association Rule Mining", International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 3, Issue 1, January–February2013,pp. 2065-2069.
Index Terms

Computer Science
Information Sciences

Keywords

Association rules Data mining Frequent Item set Mining FP growth Minimum Support