Towards a Semantic Search Engine for Scientific Articles

被引：3
|
作者：
Latard, Bastien [1 ,2 ]
Weber, Jonathan [1 ]
Forestier, Germain [1 ]
Hassenforder, Michel [1 ]
机构：
[1] Univ Haute Alsace, MIPS, Mulhouse, France
[2] MDPI AG, Basel, Switzerland
来源：
RESEARCH AND ADVANCED TECHNOLOGY FOR DIGITAL LIBRARIES (TPDL 2017) | 2017年 / 10450卷
关键词：
D O I：
10.1007/978-3-319-67008-9_54
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Because of the data deluge in scientific publication, finding relevant information is getting harder and harder for researchers and readers. Building an enhanced scientific search engine by taking semantic relations into account poses a great challenge. As a starting point, semantic relations between keywords from scientific articles could be extracted in order to classify articles. This might help later in the process of browsing and searching for content in a meaningful scientific way. Indeed, by connecting keywords, the context of the article can be extracted. This paper aims to provide ideas to build such a smart search engine and describes the initial contributions towards achieving such an ambitious goal.
引用
收藏
页码：608 / 611
页数：4
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