Random Articles
Reseach Article
Association Rule Mining Algorithm’s Variant Analysis
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 78 - Number 14 |
| Year of Publication: 2013 |
| Authors: Prince Verma, Dinesh Kumar |
10.5120/13593-1366
|
Prince Verma, Dinesh Kumar . Association Rule Mining Algorithm’s Variant Analysis. International Journal of Computer Applications. 78, 14 ( September 2013), 26-34. DOI=10.5120/13593-1366
Abstract
Association rule mining is a vital technique of data mining which is of great use and importance. For Association Rule mining various new techniques have been developed but concept for the newly developed algorithms remains the same. These recent developments are basically modifications to previous ones which introduce some minute changes in existing algorithms for better results. This paper addresses these basic algorithms and techniques in an elaborative way. So the reader can understand each of these techniques along with their pros and cons, without any additional effort. The techniques discussed here involve AIS, SETM, Apriori and FP-tree in detail.
References
- R. Agrawal, T. Imielinski, and A. N. Swami, 1993. Mining association rules between sets of items in large databases. ACM SIGMOD International Conference on Management of Data, Washington, D. C. , pp 207-216.
- U. Fayyad, G. Piatetsky-Shapiro and P. Smyth, 1996. From data mining to knowledge discovery: an overview. Advances in Knowledge Discovery and Data Mining, MIT Press, Cambridge, MA.
- U. Fayyad, S. G. Djorgovski and N. Weir, 1996. Automating the analysis and cataloging of sky surveys. Advances in Knowledge Discovery and Data Mining, MIT Press, Cambridge, MA, pp. 471-94.
- 1997. Technology Forecast, Price Waterhouse World Technology Center, Menlo Park, CA.
- M. S. Chen, J. Han, and P. Yu, 1996. Data mining: an overview from a database perspective. IEEE Transactions on Knowledge and Data Engineering, vol. 8, no. 6, pp. 866-883.
- Rakesh Agarwal, Ramakrishna Srikant, 1994. Fast Algorithm for mining association rules. VLDB Conference Santiago, Chile, pp 487-499.
- S. A. Abaya, 2012. Association Rule Mining based on Apriori Algorithm in Minimizing Candidate generation. International Journal of Scientific & Engineering Research, vol-3, issue 7.
- Sotiris Kotsiantis, Dimitris Kanellopoulos, 2006. Association Rules Mining: A Recent Overview. GESTS International Transactions on Computer Science and Engineering, vol. 32 (1), pp. 71-82.
- JaiWei Han, Jian Pei, Yiwen Yin & Runying Mao, 2004. Mining frequent patterns without candidate generation: A Frequent pattern tree approach. Data mining and knowledge discovery, Netherlands, pp 53-87.
- Huan Wu, Zhigang Lu, Lin Pan, Rong Seng XU and Wenbao jiang, 2009. An improved Apriori based algorithm for association rule mining. IEEE Sixth international conference on fuzzy systems and knowledge discovery, pp 51-55.
- Farah Hanna AL-Zawaidah, Yosef Hasan Jbara and Marwan AL-Abed Abu-Zanana, 2011. An improved Algorithm for mining Association Rule in large database. World of Computer and Information technology, vol. 1, no. 7, pp 311-316.
- Zhuang Chen, Shibang Cai, Quilin Song, Chonglai Zhu, 2011. An Improved Apriori Algorithm based on pruning Optimization and transaction reduction. IEEE transactions on evolutionary computation, pp 1908-1911.
- Suhani Nagpal, 2012. Improved Apriori Algorithm using logarithmic decoding and pruning. International Journal of Engineering Research and Applications, vol. 2, issue 3, pp. 2569-2572.
- M. Suman, T. Anuradha, K. Gowtham, A. Ramakrishna, 2012. A frequent pattern mining algorithm based on FP-tree structure and Apriori algorithm. International Journal of Engineering Research and Applications, vol. 2, issue 1, pp. 114-116.
- Sang Jun Lee, Keng Siau, 2001. A review of data mining techniques. Industrial Management and Data Systems, University of Nebraska-Lincoln Press, USA, pp 41-46.
- R. Patel Nimisha, Sheetal Mehta, 2013. A Survey on Mining Algorithms. International Journal of Soft Computing and Engineering, vol. 2, issue 6, pp 460-463.
Index Terms
Keywords