Data Mining Based Recommendation System using Social Websites

被引:4
|
作者
Ali, Faryal [1 ]
Ahmad, Tauqir [1 ]
Martinez-Enriquez, A. M. [2 ]
Muhammad, Aslam [1 ]
机构
[1] UET, Dept CS&E, Lahore, Pakistan
[2] CINVESTAV, IPN, Dept CS, Mexico City, DF, Mexico
关键词
social networking sites; data mining; recommendation system; collaborative content filtering;
D O I
10.1109/WI-IAT.2015.78
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Nowadays, social networking sites have become part of daily life to increase personal profile on line to manage contact with friends. Recommendation systems with limited or excess data use data from social networking sites for resolving common problems. This paper describes a standalone recommendation system that finds relationship between users' connections on social networking sites and preferred items. The designed Web based recommendation system collects and transforms data from social networking sites, applying content and collaborative filtering techniques. For instance, to recommend books, the system treats data from Facebook. The experimental results show that these relationships enhance the quality of proposed recommendation.
引用
收藏
页码:365 / 368
页数:4
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