Link Scientific Publications using Linked Data

被引：0

作者：

Miao, Qingliang ^{[1
]}

Meng, Yao ^{[1
]}

Fang, Lu ^{[1
]}

Nishino, Fumihito ^{[2
]}

Igata, Nobuyuki ^{[2
]}

机构：

[1] Fujitsu R&D Ctr CO LTD, Beijing 100025, Peoples R China

[2] Fujitsu Labs LTD, Nakahara Ku, Kawasaki, Kanagawa 2118588, Japan

来源：

2015 IEEE 9TH INTERNATIONAL CONFERENCE ON SEMANTIC COMPUTING (ICSC) | 2015年

关键词：

Linked Data; Entity Linking; Scientific Publication;

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：

Scientific publication management services are changing drastically. On the one hand, researchers demand intelligent search services to discover scientific publications. On the other hand, publishers need to incorporate semantic information to better organize their digital assets and make publications more discoverable. For this purpose, we investigate how to manage scientific publications using Linked Data and introduce FELinker, an entity linking component that links scientific publications with DBPedia. In particular, this paper introduces advantages of linking scientific publications with Linked Data, discusses major challenges, and outlines the proposed method. Experiment shows the proposed method could get promising performance in scientific publication linkage.

引用

页码：268 / 271

页数：4

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