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Method mention extraction from scientific research papers

机译:从科研论文中提取方法提要

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Scientific publications contain many references to method terminologies used during scientific experiments. New terms are constantly created within the research community, especially in the biomedical domain where thousands of papers are published each week. In this study we report our attempt to automatically extract such method terminologies from scientific research papers, using rule-based and machine learning techniques. We first used some linguistic features to extract fine-grained method sentences from a large biomedical corpus and then applied well established methodologies to extract the method terminologies. We focus the present study on the extraction of method phrases that contain an explicit mention of method keywords such as (algorithm, technique, analysis, approach and method) and other less explicit method terms such as Multiplex Ligation dependent Probe Amplification. Our initial results show an average F-score of 91.89 for the rule-based system and 78.26 for the Conditional Random Field-based machine learning system.
机译:科学出版物包含许多在科学实验中使用的方法术语的参考。在研究社区内,特别是在生物医学领域,不断创造新的术语,每周发表数千篇论文。在这项研究中,我们报告了我们使用基于规则的和机器学习技术从科学研究论文中自动提取此类方法术语的尝试。我们首先使用一些语言功能从大型生物医学语料库中提取细粒度的方法语句,然后应用完善的方法学来提取方法术语。我们将本研究的重点放在方法短语的提取上,这些方法短语包含方法关键字的明确提及,例如(算法,技术,分析,方法和方法)以及其他不太明确的方法术语,例如依赖于多重连接的探针扩增。我们的初步结果显示,基于规则的系统的平均F得分为91.89,而基于条件随机场的机器学习系统的平均F得分为78.26。

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