원문정보
보안공학연구지원센터(IJHIT)
International Journal of Hybrid Information Technology
Vol.8 No.11
2015.11
pp.121-138
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
A novel approach for the efficient weighted association rule mining proposed in this present paper. The proposed approach reducts the transactional dataset (weighted) by utilizing the power of Rough Set theory. Furthermore, proposed approach acquires the benefit for weighted measures (w-support, w-confidence) for obtaining the most profitable weighted frequent itemsets and the Genetic Algorithm for the extracting the desired set of optimized weighted association rules. Experimental analysis of proposed approach has been done and observed that the approach works well and will be helpful in situation when there is a requirement for the consideration of extracting the best weighted association rules in decision-making process.
목차
Abstract
1. Introduction
2. Related Works
2.1. Rough Set Theory
2.2. Weighted Association Rules Mining
2.3. Genetic Algorithm
3. Proposed Method
3.1. Proposed Algorithm:
4. Experimental Analysis
4.1. Comparative Study and Results
4.2. Execution Time
4.3. Number of Association Rules
5. Conclusion
References
1. Introduction
2. Related Works
2.1. Rough Set Theory
2.2. Weighted Association Rules Mining
2.3. Genetic Algorithm
3. Proposed Method
3.1. Proposed Algorithm:
4. Experimental Analysis
4.1. Comparative Study and Results
4.2. Execution Time
4.3. Number of Association Rules
5. Conclusion
References
키워드
저자정보
참고문헌
자료제공 : 네이버학술정보