TAILIEUCHUNG - Summary of Computer doctoral thesis: Mining weighted sequential patterns in sequence database

The objective of the thesis is to propose a solution to mine the weighted sequential patterns between sequences in sequence databases with time interval and quantitative sequence databases with time interval. | MINISTRY OF EDUCATION VIETNAM ACADEMY OF AND TRAINING SIENCE AND TECHNOLOGY GRADUATE UNIVERSITY OF SIENCE AND TECHNOLOGY . . TRAN HUY DUONG MINING WEIGHTED SEQUENTIAL PATTERNS IN SEQUENCE DATABASE Major Information System Major code 62 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 Dr. Nguyen Truong Thang Supervisor 2 Prof. Dr. Vu Duc Thi Reviewer 1 Reviewer 2 Reviewer 3 . The thesis shall be defended in front of the Thesis Committee at Vietnam Academy Of Science And Technology - Graduate University Of Science And Technology at . hour date month . year 2021 This thesis could be found at - The National Library of Vietnam - The Library of Graduate University of Science and Technology INTRODUCTION 1. Overview Mining frequent sequence patterns is one of the important issues and is studied by many scholars in the field of data mining. Sequential pattern mining has many real-life applications since data is encoded as sequences in many fields such as bioinformatics e-learning market basket analysis text analysis and webpage click-stream analysis. This field of research has emerged in the 1990s with the seminal paper of Agrawal and Srikant 2 . Usually the sequential pattern mining does not include additional information. Meanwhile the expansion of the information of the data series is very diverse such as adding information about the weights of the items in the sequence information about the quantity of the items in the sequence information about the time interval. For sequence databases with the time interval the time interval of the occurrence of data series allows analysis of how long after the sequence patterns will appear. The studies so far have focused on detecting time-spaced sequence patterns that occur between components in time-spaced sequence databases where the time interval is a well-defined numerical value. .

• Thạc sĩ - Tiến sĩ - Cao học
• Summary of Computer doctoral thesis
• Information system
• Sequence database
• Mining weighted sequential patterns
• Cơ sở dữ liệu dãy
• Hệ thống thông tin
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• Control mechanisms
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• Luận án Tiến sĩ Công nghệ thông tin
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