Dòng Nội dung
1
Content based image retrieval using multiple features and pareto approach / Vu Van Hieu, Nguyen Truong Thang, Nguyen Huu Quynh, Ngo Quoc Tao // Tạp chí Tin học và Điều khiển học . - 2016. - P. 169-187. - ISSN:


19 p.
Ký hiệu phân loại (DDC): 005
In this paper the authors propose to use pareto approach for candidate selection, the proposed algorithm produces a compact set of candidate images when comparing with the entire datase and this set also contains results obtained from all aggregation operator
 Số bản sách: (0) Tài liệu số: (1)
2
Mining top-k frequent sequential pattern in item Interval extended sequence database / Tran Huy Duong, Nguyen Truong Thang, Vu Duc Thi, Tran Thế Anh // Tạp chí Tin học và Điều khiển học = Journal of Computer Science And Cybernetics . - 2018. - Pages 249 - 263. - ISSN:


16 p.
Ký hiệu phân loại (DDC): 005
Frequent sequential pattern mining in item interval extended sequence database (ỉSDB) has been one of the interesting tasks in recent years. Unlike classic frequent sequential pattern mining. The pattern mining in ISDB also consider the item interval between successive items thus it may extract more meaningful sequential patterns in real life. Most previous frequent sequential pattern mining in ISDB algorithms needs a minimum support threshold (min sup) to perform the mining . However, it’s not easy for use to provide an appropriate threshold in practice. The too high min sup value will lead to missing valuable patterns. while the too low min sup value may generate too many useless patterns. To address this problem we propose an algorithm: Top KWFP — top K weighted frequent sequential pattern mining in item interval extended sequence database. Our algorithm doesn't needs to provide a fixed min sup value. This min sup value will dynamically raise during the mining process.
Số bản sách: (0) Tài liệu số: (0)