Phrase-based Semantic Textual Similarity for Linking Researchers

被引：0
|
作者：
Reyes-Ortiz, Jose A. [1 ]
Bravo, Maricela [1 ]
Padilla, Omar E. [1 ]
机构：
[1] Metropolitan Autonomous Univ, Dept Syst, Mexico City, DF, Mexico
来源：
2015 26TH INTERNATIONAL WORKSHOP ON DATABASE AND EXPERT SYSTEMS APPLICATIONS (DEXA) | 2015年
关键词：
Semantic Textual Similarity; Ontology Knowledge Representation; Natural Language Processing; Researchers Linking;
D O I：
10.1109/DEXA.2015.54
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Researchers need to establish networks with colleagues that work similar topics, frequently; they are looking similar works by exploring free text in scientific publications in order to update them with the recent state of the art. They read the abstracts and decide whether or not it is a related and relevant work. Therefore, this paper presents an approach for linking researchers based on measuring the similarity between the abstracts of their scientific publications in English. Our approach discovers ontological relationships between free text scientific publications using statistical and semantic similarity measures. An evaluation of a gold standard data set is presented, it has shown an average of 0.6399 for Pearson product-moment correlation coefficient.
引用
收藏
页码：202 / 206
页数：5
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