Creation of Individual Scientific Concept-Centered Semantic Maps Based on Automated Text-Mining Analysis of PubMed.

Q1 Biochemistry, Genetics and Molecular Biology Advances in Bioinformatics Pub Date : 2018-07-26 eCollection Date: 2018-01-01 DOI:10.1155/2018/4625394
Ekaterina Ilgisonis, Andrey Lisitsa, Valerya Kudryavtseva, Elena Ponomarenko
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Abstract

Concept-centered semantic maps were created based on a text-mining analysis of PubMed using the BiblioEngine_v2018 software. The objects ("concepts") of a semantic map can be MeSH-terms or other terms (names of proteins, diseases, chemical compounds, etc.) structured in the form of controlled vocabularies. The edges between the two objects were automatically calculated based on the index of semantic similarity, which is proportional to the number of publications related to both objects simultaneously. On the one hand, an individual semantic map created based on the already published papers allows us to trace scientific inquiry. On the other hand, a prospective analysis based on the study of PubMed search history enables us to determine the possible directions for future research.

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基于PubMed自动文本挖掘分析的个体科学概念中心语义图的创建。
基于PubMed的文本挖掘分析,使用BiblioEngine_v2018软件创建了以概念为中心的语义图。语义图的对象(“概念”)可以是MeSH术语或以受控词汇表形式构建的其他术语(蛋白质、疾病、化合物等的名称)。基于语义相似性指数自动计算两个对象之间的边缘,该指数与同时与两个对象相关的出版物数量成比例。一方面,基于已经发表的论文创建的个体语义图使我们能够追踪科学探究。另一方面,基于PubMed搜索历史研究的前瞻性分析使我们能够确定未来研究的可能方向。
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来源期刊
Advances in Bioinformatics
Advances in Bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (miscellaneous)
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