Appling Association Rule to Web Prediction

Author

Zhang, Zhili ; Shi, Lei ; Guo, Shen ; Qi, Deyu ; Li, Fufang

Author_Institution

Comput. Network Center, Xuchang Univ.

Volume

2

fYear

2006

fDate

20-24 June 2006

Firstpage

522

Lastpage

527

Abstract

With the rapid development of the Internet, Web log mining, which is used to find useful information about users from Web log files, has become a heat issue of research. The aim of association rule mining is to find interesting and useful patterns in a transaction base. This paper makes use of variable precision rough set theory to retrieve the associated rules from Web log and applies the rules to the prediction of users´ behaviors. Experiments indicate that the prediction precision is better than those existing methods

Keywords

Internet; data mining; information retrieval; rough set theory; Internet; Web log files; Web log mining; Web prediction; association rule extraction; association rule mining; data mining; user behavior prediction; variable precision rough set theory; Association rules; Classification tree analysis; Computer networks; Computer science; Data mining; Heat engines; IP networks; Set theory; Web mining; Web page design; Web mining; association rules.; rough set; web log;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Computational Sciences, 2006. IMSCCS '06. First International Multi-Symposiums on

Conference_Location

Hanzhou, Zhejiang

Print_ISBN

0-7695-2581-4

Type

conf

DOI

10.1109/IMSCCS.2006.193

Filename

4673759