DocumentCode :
2827288
Title :
Research on browsing pattern of group users based on ACO
Author :
Liu, Qinghua ; Huang, Minghe ; Guo, Bin ; Chen, Na
Author_Institution :
Sch. of Software, Jiangxi Normal Univ., Nanchang, China
Volume :
5
fYear :
2010
fDate :
22-24 Oct. 2010
Abstract :
It is urgent to solve the problem of how to accurately understand users´ behaviors of visiting websites in the development of e-commerce. Web log mining is an important research method in addressing the problem. In this paper, we propose the new concept of interest pheromone, and on the basis of which design a group users´ navigation path mining algorithm based on ant colony algorithm. The experimental result shows that interest pheromone can efficiently track users´ changes of interests. It can accurately reflect users´ browsing mode when introduced in the algorithm of the paper.
Keywords :
data mining; electronic commerce; online front-ends; optimisation; ACO; Web log mining; Web sites; ant colony algorithm; browsing pattern; e-commerce; group user navigation path mining algorithm; user browsing mode; Computational modeling; Browsing mode; ant colony algorithm; interest pheromone; web log mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Application and System Modeling (ICCASM), 2010 International Conference on
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4244-7235-2
Electronic_ISBN :
978-1-4244-7237-6
Type :
conf
DOI :
10.1109/ICCASM.2010.5620031
Filename :
5620031
Link To Document :
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