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Method for automatic key concepts extraction: Application to documents in the domain of nuclear reactors

机译:自动关键概念提取方法:应用于核反应堆领域的文档

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Purpose Ontology of a domain mainly consists of a set of concepts and their semantic relations. It is typically constructed and maintained by using ontology editors with substantial human intervention. It is desirable to perform the task automatically, which has led to the development of ontology learning techniques. One of the main challenges of ontology learning from the text is to identify key concepts from the documents. A wide range of techniques for key concept extraction have been proposed but are having the limitations of low accuracy, poor performance, not so flexible and applicability to a specific domain. The propose of this study is to explore a new method to extract key concepts and to apply them to literature in the nuclear domain.Design/methodology/approach In this article, a novel method for key concept extraction is proposed and applied to the documents from the nuclear domain. A hybrid approach was used, which includes a combination of domain, syntactic name entity knowledge and statistical based methods. The performance of the developed method has been evaluated from the data obtained using two out of three voting logic from three domain experts by using 120 documents retrieved from SCOPUS database.Findings The work reported pertains to extracting concepts from the set of selected documents and aids the search for documents relating to given concepts. The results of a case study indicated that the method developed has demonstrated better metrics than Text2Onto and CFinder. The method described has the capability of extracting valid key concepts from a set of candidates with long phrases.Research limitations/implications The present study is restricted to literature coming out in the English language and applied to the documents from nuclear domain. It has the potential to extend to other domains also.Practical implications The work carried out in the current study has the potential of leading to updating International Nuclear Information System thesaurus for ontology in the nuclear domain. This can lead to efficient search methods.Originality/value This work is the first attempt to automatically extract key concepts from the nuclear documents. The proposed approach will address and fix the most of the problems that are existed in the current methods and thereby increase the performance.
机译:域的目的本体主要包括一组概念及其语义关系。它通常通过使用具有实质性干预的本体编辑器来构造和维护。希望自动执行任务,这导致了本体学习技术的开发。本体学习从文本中学习的主要挑战之一是识别文件中的关键概念。已经提出了适用于关键概念提取的各种技术,但具有低精度,性能差,不灵活,对特定领域的适用性具有局限性。本研究的建议是探讨提取关键概念的新方法,并将它们应用于核目中的文学。在本文中,提出了一种新的关键概念提取方法,并从事文件核领域。使用混合方法,其中包括域,语法名称实体知识和基于统计方法的组合。已经通过使用从Scopus Database检索的120个文件中使用的三个域专家中的三个投票逻辑中的两个从三个域专家中获得的数据进行了评估的性能。文件报告的工作与从所选文件集中提取概念并辅助搜索与给定概念有关的文件。案例研究的结果表明,该方法开发的方法比Text2onto和CFinder展示了更好的指标。所描述的方法具有从具有长短语的一组候选者提取有效关键概念的能力。研究限制/影响本研究仅限于英语语言的文学,并应用于核领域的文件。它还可能延伸到其他领域。正常意义当前研究中开展的工作有可能导致在核领域进行国际本体的国际核信息系统叙述。这可能导致有效的搜索方法。重要/价值这项工作是第一次尝试从核文件中自动提取关键概念。所提出的方法将解决并修复当前方法中存在的大多数问题,从而提高性能。

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