Title :
User interest discovery based on Web Usage Mining
Author :
Bin, Jia ; Jian-guo, Xu ; Xu, Chang
Author_Institution :
College of Information and Engineering, Shan Dong University of Science and Technology, Qingdao. China
Abstract :
According to the user´s access sequence, whether clustering can extracte the effectively user´s interest model is closely related to the algorithm of identifying user´s access affairs and clustering. This paper fully consider the impact on user interest mining of the topology and order of web papers. So, this paper advanced AER algorithm, new similarity formula and FCR algorithm. Finally, this paper tested and verified the AER algorithm and FCR algorithm.
Keywords :
Clustering algorithms; Computational modeling; Computer integrated manufacturing; Computers; Data mining; Data models; Educational institutions; clustering; similarity; user interest discovery; web usage mining;
Conference_Titel :
E -Business and E -Government (ICEE), 2011 International Conference on
Conference_Location :
Shanghai, China
Print_ISBN :
978-1-4244-8691-5
DOI :
10.1109/ICEBEG.2011.5886765
