Usage Profile based Recommendation system

被引：0
|
作者：
Thiyagarajan, R. [1 ]
Thangavel, K. [2 ]
Rathipriya, R. [2 ]
机构：
[1] Nehru Inst IT & Management, Dept Comp Applicat, Coimbatore 641105, Tamil Nadu, India
[2] Periyar Univ, Dept Comp Sci, Salem 636011, India
来源：
2014 INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING APPLICATIONS (ICICA 2014) | 2014年
关键词：
Web Usage Mining; K-Means clustering; Recommendations; Hamming distance; Mean square residue; INFORMATION; WEB;
D O I：
10.1109/ICICA.2014.84
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Web Usage Mining (WUM) is used to analyze the web user behavior and navigation pattern by the automatic discovery of the web user patterns. Presently WUM has been widely used in building the recommendation systems. Web recommendation system is a specific type of information filtering system that aims to predict the user next browsing activity and then recommend to the user web pages items that are likely to be of interest to the user. In this paper, a new recommendation system is proposed to predict the user's navigational behavior. The practical implementation of this algorithm shows that the prediction of user intuition capturing is more accurate.
引用
收藏
页码：382 / 386
页数：5
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