Comparison of Group Recommendation Techniques in Social Networks

被引：0

作者：

Minaei-Bidgoli, Behrouz ^{[1
]}

Esmaeili, Leila ^{[2
]}

Nasiri, Mahdi ^{[3
]}

机构：

[1] Iran Univ Sci & Technol, Dept Comp Engn, Tehran, Iran

[2] Univ Qom, Qom, Iran

[3] Iran Univ Sci & Technol, Tehran, Iran

来源：

2011 1ST INTERNATIONAL ECONFERENCE ON COMPUTER AND KNOWLEDGE ENGINEERING (ICCKE) | 2011年

关键词：

social network; recommender system; content based filtering; collaborative filtering; hybrid; SYSTEM;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Virtual communities and groups are known as one of the features of social networks for creating the possibility for users to join together and interact. Regarding the growth of social networks as well as attracting new users of various ages and creation of different groups, assisting users seems quite necessary. Along with studying some of the common recommender methods in social networks in this paper, a new method is explained. This new method is designed using d-tree classification, association rules and the concepts of information theory which compared with others, it gives better results. It is also possible in this system to offer recommendations to new users who have just joined the network and do not have any links.

引用

页码：236 / 241

页数：6

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