Title :
A Multi-Supports-Based Sequential Pattern Mining Algorithm
Author :
Xiong, Yun ; Zhu, Yang-yong
Author_Institution :
Dept. of Comput. & Inf. Technol., Fudan Univ., Shanghai
Abstract :
Sequential pattern mining is now widely used in various areas, such as the analysis of biological sequences, Web access patterns, customer purchase patterns and etc. In this paper, we propose a new definition for M-sequences. Also we present multiple supports: local support, total support, and distribution support for their related mining of local sequential patterns, total sequential patterns and existence sequential patterns. Based on multiple supports, a multi-supports-based sequential pattern mining algorithm is developed which can be generally applied to find such patterns
Keywords :
data mining; pattern recognition; Web access pattern; biological sequences; customer purchase pattern; multisupport-based sequential pattern mining algorithm; Algorithm design and analysis; Biology computing; Data mining; Design optimization; Frequency; Information analysis; Information technology; Pattern analysis; Web page design;
Conference_Titel :
Computer and Information Technology, 2005. CIT 2005. The Fifth International Conference on
Conference_Location :
Shanghai
Print_ISBN :
0-7695-2432-X
DOI :
10.1109/CIT.2005.22
