Title :
Web prediction using online support vector machine
Author :
Zhang, Zhili ; Guo, Changgeng ; Yu, Shu ; Qi, Deyu ; Long, Songqian
Author_Institution :
Coll. of Comput. Sci. & Eng., South China Univ. of Technol., Guangzhou
Abstract :
In this paper, a SVM-based online learning algorithm is proposed and applied to the problem of Web prediction. A method to construct an online LS-SVM multi-class learning model has been presented. This method is able to capture the inherent sequentiality of Web visits and successfully predict the future accesses. The experimental results show the effective performance of our method
Keywords :
Internet; learning (artificial intelligence); support vector machines; SVM-based online learning algorithm; Web prediction; Web visit sequentiality; online LS-SVM multiclass learning model; online support vector machine; Computer networks; Educational institutions; History; Information science; Network servers; Support vector machine classification; Support vector machines; Telecommunication traffic; Web server; World Wide Web; Web prediction; multi-class; online learning; support vector machine;
Conference_Titel :
Tools with Artificial Intelligence, 2005. ICTAI 05. 17th IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
0-7695-2488-5
DOI :
10.1109/ICTAI.2005.128
