Introducing Docear's Research Paper Recommender System

被引：0

作者：

Beel, Joeran ^{[1
]}

Langer, Stefan ^{[1
]}

Genzmehr, Marcel ^{[1
]}

Nuernberger, Andreas ^{[2
]}

机构：

[1] Docear, Magdeburg, Germany

[2] OvGU, FIN, DKE Grp, Magdeburg, Germany

来源：

JCDL'13: PROCEEDINGS OF THE 13TH ACM/IEEE-CS JOINT CONFERENCE ON DIGITAL LIBRARIES | 2013年

关键词：

recommender systems; user model; mind map; mind mapping; research paper recommender system; content-based filtering;

D O I：

暂无

中图分类号：

G25 [图书馆学、图书馆事业]; G35 [情报学、情报工作];

学科分类号：

1205 ; 120501 ;

摘要：

In this demo paper we present Docear's research paper recommender system. Docear is an academic literature suite to search, organize, and create research articles. The users' data (papers, references, annotations, etc.) is managed in mind maps and these mind maps are utilized for the recommendations. Using content-based filtering methods, Docear's recommender achieves click-through rates around 6%, in some scenarios even over 10%.

引用

页码：459 / 460

页数：2

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