tailieunhanh - Summary of Computer doctoral thesis: Mining fuzzy association rules and fuzzy sequential patterns in temporal quantitative databases

The objective of the thesis: Mining association rules with time-interval between events in temporal quantitative databases called fuzzy time-interval association rules; mining sequential patterns with time-interval between events in temporal quantitative sequential databases called fuzzy sequential patterns with fuzzy time intervals; mining common sequential rules with time-interval between events in temporal quantitative sequential databases called fuzzy common sequential rules with fuzzy time intervals. | MINISTRY OF EDUCATION AND VIETNAM ACADEMY TRAINING OF SCIENCE AND TECHNOLOGY GRADUATE UNIVERSITY SCIENCE AND TECHNOLOGY - TRUONG DUC PHUONG MINING FUZZY ASSOCIATION RULES AND FUZZY SEQUENTIAL PATTERNS IN TEMPORAL QUANTITATIVE DATABASES Major Information Systems Code 9 48 01 04 SUMMARY OF COMPUTER DOCTORAL THESIS Ha Noi 2021 The thesis has been completed at Graduate University Of Science And Technology - Vietnam Academy Of Science And Technology Supervisor 1. Assoc. Prof. Dr. Do Van Thanh Supervisor 2. Assoc. Prof. Dr. Nguyen Duc Dung Review 1 Review 2 Review 3 The thesis will be defended at the Board of Examiners of Graduate University Of Science And Technology - Vietnam Academy Of Science And Technology at .on . The thesis can be explored at - Library of Graduate University Of Science And Technology - National Library of Vietnam INTRODUCTION 1. Motivation of the thesis Phương and Thành 2013 Mining association rules and sequential patterns sequential rules are some of the most important domains in data mining. Up to now a lot of research related to them. Association rules and sequential patterns sequential rules are proposed in many forms such as transaction quantitative weighted unweighted with without time etc. Rekesh Agrawal et al first introduced an association rule mining problem in transaction databases in 1993 Agrawal Imieliński and Swami 1993 and up to now there have been many proposed algorithms according to many different approaches to mining the rules in transaction databases such as APRIORI Agrawal Srikant and others 1994 PARTITION Savasere Omiecinski and Navathe 1995 A-CLOSE Pasquier et al. 1999a A-CLOSE Shekofteh Rahmani and Dezfuli 2008 CLOSE Pasquier et al. 1999b CLOSET Pei et al. 2000 CLOSET Wang Han and Pei 2003 CHARM Zaki and Hsiao 2002 MAFIA Burdick Calimlim and Gehrke 2001 GENMAX Gouda and Zaki 2005 ECLAT Ogihara et al. 1997 DIC Brin et al. 1997 FP-GROWTH Han et al. 2004 CFPMINE Qin Luo and Shi 2004 ETARM Nguyen et al. 2018 LRM Saravanan and .

• Thạc sĩ - Tiến sĩ - Cao học
• Temporal quantitative databases
• Summary of Computer doctoral thesis
• Computer doctoral
• Fuzzy sequential patterns
• Mining fuzzy association rules
• Information technology
• Information technology doctoral thesis
• Linguistic information
• Mathematical foundation for informatics
• Data mining
• Association rules
• Compressed transactions
• Knowledge discovery
• Hedge algebras