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Mining Positive and Negative Association Rule from Frequent and Infrequent Pattern based on IMLMS_GA
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 77 - Number 14 |
| Year of Publication: 2013 |
| Authors: Nikky Rai, Susheel Jain, Anurag Jain |
10.5120/13555-1393
|
Nikky Rai, Susheel Jain, Anurag Jain . Mining Positive and Negative Association Rule from Frequent and Infrequent Pattern based on IMLMS_GA. International Journal of Computer Applications. 77, 14 ( September 2013), 48-52. DOI=10.5120/13555-1393
Abstract
Association rule mining is one of the most significant tasks in data mining. The essential concept of association rule is to mine the positive patterns from transaction database. But mining the negative patterns has also received the interest of publishers in this region. This paper shows an efficient algorithm (IMLMS-GA) for mining both positive and negative association rules in transaction databases. The goal of this study is to build up a new model for mining negative and positive (PR & NR) association rules out of transaction data sets. The proposed model is based on two models, the MLMS model and the Interesting Multiple Level Minimum Supports (IMLMS) model. This paper proposes a new approach (IMLMS-GA) for mining both negative and positive association rules. The interesting frequent patterns and infrequent patterns mined by the IMLMS-GA algorithm. This algorithm is accomplished in two phase: a. First phase find all frequent patterns & infrequent patterns b. Second phase efficiently generate positive and negative association rule by using useful frequent pattern set. The experimental results prove that the IMLMS-GA can remove the scale of uninteresting association rules and generates better results than the previous positive and negative association rule mining algorithm.
References
- Agrawal R, Imielinski T, Swami A (1993)"Mining Association Rules between Sets of Items in Large Databases" . In Proceeding of the ACM SIGMOD International conference on Management of Data, Washington DC,ACM ,pp207-216.
- Yanguang Shen, Jie Liu, Zhiyong yang (2009) "Research on Positive and Negative Association Rules based on Interest Support confidence framework". Published in computational intelligence and software engineering CiSE 2009, IEEE, pp 1- 4
- Shi-ju Shang, Xiang –jun Dong ,Jie Li,Yuan-yuan Zhao (2008) "Mining Positive and Negative Association Rules in multi-database based on Minimum Interestingness". Published in Intelligent Computation Technology and Automation (ICICTA) 'International Conference Volume 1', IEEE, pp 791-794.
- He Jiang, Yuanyuan Zhao, Chunhua Yang, Xiangjun Dong (2008) "Mining both Positive and Negative Weighted Association Rules with Multiple Minimum Supports". Published in International conference volume 4, Computer science & software Engineering CiSE, IEEE, pp407-410.
- By Xiufend Piao, Zhan long Wang, Gang Liu (2011) "Research on Mining Positive and Negative Association Rules based on dual confidence". Internet computing for Science & Engineering ICICSE, IEEE,pp102-105.
- Wu, X. , Zhang, C. , Zhang, S (2004) "Efficient Mining of both Positive and Negative Association Rules". ACM Transactions on Information Systems 22(3): pp 381–405.
- By Idheba Mohamad Ali O,Swesi ,Azuraliza Abu Bakar, Anis Suhailis Abdul Kadir(2012) "Mining Positive and Negative Association Rules from Interesting Frequent and Infrequent Itemsets". 9th international conference on Fuzzy Systems and Knowledge Discovery (FSKD), IEEE pp 650-655
- By Sandeep Kumar, K. Srinivas, Peddi Kishor, and T. Bhaskar (2011) "An Alternative Approach to mine Association Rules". Electronics Computer Technology (ICECT),3rd international conference volume 6, IEEE pp 420-424.
- By Chun-Hao-Chen, tzung-Pei Hong and Yeong Chy Lee (2011)"A Multiple level genetic Fuzzy Mining Algorithm". International Conference on Fuzzy System (FUZZ), IEEE, pp 278-282.
- By Xiangjun Dong (2011) "Mining Interesting frequent and frequent itemsets based on minimum correlation strength" @ Springer- Verlag Berlin Hedelberg.
- By Xiangjun Dong, Zhiyun Zheng ,Zhendong Niu, Donghua Zhu,Qiuting Jia(2008) "Mining Interesting Infrequent and frequent itemsets based on MLMS model ". The fourth international conference on advanced data mining and application ,ADMA 5139. 444-451, IEEE pp 444-451 .
- C. F. Lima,M. Pelikan,D. Goldberg. K. S. O. G. Lobo(2008)"Influence of Selection and Replacement strategies on linkage learning in bao. CEC 2007 IEEE pp 1083-1090
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