SoPRa: A New Social Personalized Ranking Function for Improving Web Search

被引：0

作者：

Reda, Mohamed ^{[1
]}

Hacid, Hakim ^{[2
]}

Bouzeghoub, Mokrane ^{[1
]}

机构：

[1] Versailles Univ, PRiSM Lab, Versailles, France

[2] Sidetrade, F-92100 Boulogne, France

来源：

SIGIR'13: THE PROCEEDINGS OF THE 36TH INTERNATIONAL ACM SIGIR CONFERENCE ON RESEARCH & DEVELOPMENT IN INFORMATION RETRIEVAL | 2013年

关键词：

Information Retrieval; Social networks;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We present in this paper a contribution to IR modeling by proposing a new ranking function called SoPRa that considers the social dimension of the Web. This social dimension is any social information that surrounds documents along with the social context of users. Currently, our approach relies on folksonomies for extracting these social contexts, but it can be extended to use any social meta-data, e.g. comments, ratings, tweets, etc. The evaluation performed on our approach shows its benefits for personalized search.

引用

页码：861 / 864

页数：4

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