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
보안공학연구지원센터(IJHIT) [Science & Engineering Research Support Center, Republic of Korea(IJHIT)]
설립연도
2006
분야
공학>컴퓨터학
소개
1. 보안공학에 대한 각종 조사 및 연구
2. 보안공학에 대한 응용기술 연구 및 발표
3. 보안공학에 관한 각종 학술 발표회 및 전시회 개최
4. 보안공학 기술의 상호 협조 및 정보교환
5. 보안공학에 관한 표준화 사업 및 규격의 제정
6. 보안공학에 관한 산학연 협동의 증진
7. 국제적 학술 교류 및 기술 협력
8. 보안공학에 관한 논문지 발간
9. 기타 본 회 목적 달성에 필요한 사업
간행물
간행물명
International Journal of Hybrid Information Technology
간기
격월간
pISSN
1738-9968
수록기간
2008~2016
십진분류
KDC 505DDC 605
이 권호 내 다른 논문 / International Journal of Hybrid Information Technology Vol.8 No.11