Ấn phẩm:
Parallel fuzzy frequent itemset mining using cellular automata
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Tóm tắt
Finding frequent fuzzy itemsets in operational quantitative databases is a signifiant challenge for fuzzy association rule mining in the context of data mining. If frequent fuzzy itemsets are detected, the decision-making process and formulating strategies in businesses will be made more precise. Because the characteristic of these data models is a large number of transactions and unlimited and high-speed productions. This leads to limitations in calculating the support for itemsets containing fuzzy attributes. As a result, mining using parallel processing techniques has emerged as a potential solution to the issue of slow availability. This study presents a reinforced technique for mining frequent fuzzy sets based on cellular learning automata (CLA). The results demonstrate that frequent set mining can be accomplished with less running time when the proposed method is compared to iMFFP and NPSFF methods.
Mô tả
Journal of Computer Science and Cybernetics, Vol.38, No.4
Tác giả
Tran, T. T. Trinh
Nguyen, T.Thuan
Nguyen, L. Giang
Truong, N. Chau
Người hướng dẫn
Nơi xuất bản
Nhà xuất bản
Viện Công nghệ thông tin, Viện Hàn lâm Khoa học và Công nghệ Việt Nam
Năm xuất bản
2022-12
ISSN tạp chí
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Từ khóa chủ đề
Frequent fuzzy itemsets , Cellular automata , Parallel mining