Efficient algorithms for mining frequent weighted itemsets from weighted items databases Le B., Nguyen H., Vo B. Faculty of Information Technology, University of Science, Ho Chi Minh, Viet Nam; Faculty of Information Technology, Saigon University, Ho Chi Minh, Viet Nam; Faculty of Information Technology, Ho Chi Minh City University of Technology, Viet Nam Abstract: In this paper, we propose algorithms for mining Frequent Weighted Itemsets (FWIs) from weighted items transaction databases. Firstly, we introduce the WIT-tree data structure for mining high utility itemsets in the work of Le et al. (2009) and modify it for mining FWIs. Next, some theorems are proposed. Based on these theorems and the WIT-tree, we propose an algorithm for mining FWIs. Finally, Diffset for fast computing the weighted support of itemsets and saving memory are also discussed. We test the proposed algorithms in many databases and experimental results show that they are very efficient in comparison with Apriori-based approach. ©2010 IEEE. Author Keywords: Frequent weighted itemsets; Frequent weighted support; Weighted items transaction databases; WIT-FWIs; WIT-tree Index Keywords: Frequent weighted support; Item sets; Weighted items transaction databases; WIT-FWIs; WIT-tree; Algorithms; Data structures; Database systems; Innovation; Trees (mathematics) Year: 2010 Source title: 2010 IEEE-RIVF International Conference on Computing and Communication Technologies: Research, Innovation and Vision for the Future, RIVF 2010 Art. No.: 5632814 Link: Scorpus Link Correspondence Address: Le, B.; Faculty of Information Technology, University of Science, Ho Chi Minh, Viet Nam; email:
[email protected] Conference name: 2010 8th IEEE-RIVF International Conference on Computing and Communication Technologies: Research, Innovation and Vision for the Future, RIVF 2010 Conference date: 1 November 2010 through 4 November 2010 Conference location: Hanoi Conference code: 83982 ISBN: 9.78142E+12 DOI: 10.1109/RIVF.2010.5632814 Language of Original Document: English Abbreviated Source Title: 2010 IEEE-RIVF International Conference on Computing and Communication Technologies: Research, Innovation and Vision for the Future, RIVF 2010 Document Type: Conference Paper Source: Scopus Authors with affiliations:
1. Le, B., Faculty of Information Technology, University of Science, Ho Chi Minh, Viet Nam 2. Nguyen, H., Faculty of Information Technology, Saigon University, Ho Chi Minh, Viet Nam 3. Vo, B., Faculty of Information Technology, Ho Chi Minh City University of Technology, Viet Nam
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