Optimization of Fragment based Mining through Genetic Algorithm
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10.5120/17589-8299 |
Rajesh V Argiddi and S S Apte. Article: Optimization of Fragment based Mining through Genetic Algorithm. International Journal of Computer Applications 100(13):37-42, August 2014. Full text available. BibTeX
@article{key:article,
author = {Rajesh V. Argiddi and S. S. Apte},
title = {Article: Optimization of Fragment based Mining through Genetic Algorithm},
journal = {International Journal of Computer Applications},
year = {2014},
volume = {100},
number = {13},
pages = {37-42},
month = {August},
note = {Full text available}
}
Abstract
The approach stated in this paper mainly focuses on generating optimized rules in fragment based association mining using genetic algorithm. we call this approach as Genetic based Fragment Rule Mining. we designed a novel method for generation of optimized rule. In which a Fragment mining is used to generate the rules on which we use the optimization mechanism. This deals mainly with reducing the time and space complexity required in processing the data using fragment mining & generate strong rules using genetic algorithm. The results reported in this paper are very promising since the discovered rules are of optimized rules.
References
- Wanzhong Yang, "Granule Based Knowledge Representation for Intra and Inter Transaction Association Mining", Queensland University of Technology, July 2009
- R. V Argiddi,S. SApte " study of association rule mining in fragmented item-sets for prediction of transactions outcome in stock trading systems" IJCET-2012
- Kannika Nirai Vaani M, E Ramaraj "An integrated approach to derive effective rules from association rule mining using genetic algorithm" IEEE2013 International Conference
- Kannika Nirai Vaani M, E Ramaraj" E-Rules: An Enhanced Approach to Derive Disjunctive and useful Rules from Association Rule Mining without Candidate Item Generation" IJCA-2013
- R. Agrawal, T. Imielinski, and A. Swami. "Mining association rules between sets of items in large databases". In Proceedings of the ACM SIGMOD International Conference on Management of Data (ACM SIGMOD '93), pages 207216, Washington, USA, May 1993.
- R. V Argiddi, S. SApte " Future Trend Prediction of Indian IT Stock Market using Association Rule Mining of Transaction data" IJCA-2012.
- Anandhavalli M, Suraj Kumar Sudhanshu, Ayush Kumar and Ghose M. K. "Optimized association rule mining using genetic algorithm", Advances in Information Mining, ISSN: 0975–3265, Volume 1, Issue 2, 2009
- Prashant S. Chavan, Prof. Dr. Shrishail. T. Patil" Parameters for Stock Market Prediction" IJCTA | Mar-Apr 2013 Vol 4 (2),337-340
- Kalyanmoy Deb, "Introduction to Genetic Algorithms", Kanpur Genetic Laboratory (Kangal), Depart of Mechanical Engineering, IIIT Kanpur 2005.
- Nikhil Jain,Vishal Sharma,Mahesh Malviya "Reduction of Negative and Positive Association Rule Mining and Maintain Superiority of Rule Using Modified Genetic Algorithm" International Journal of Advanced Computer Research (ISSN (print): 2249-7277 ISSN (online): 2277-7970) Volume-2 Number-4 Issue-6 December-2012.