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Phrase-Based Semantic Textual Similarity for Linking Researchers

机译:链接研究人员基于短语的语义文本相似度

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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.
机译:研究人员需要与从事类似主题的同事建立网络,他们经常通过探索科学出版物中的自由文本来寻找相似的作品,以便以最新的技术水平对它们进行更新。他们阅读摘要并决定它是否是相关的相关工作。因此,本文提出了一种基于研究人员的英文科学出版物摘要之间相似度的链接方法。我们的方法使用统计和语义相似性度量来发现自由文本科学出版物之间的本体论关系。给出了对黄金标准数据集的评估,该数据集显示Pearson乘积矩相关系数的平均值为0.6399。

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