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首页> 外文期刊>Journal of Bioinformatics and Computational Biology >A RE-EVALUATION OF BIOMEDICAL NAMED ENTITY–TERM RELATIONS
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A RE-EVALUATION OF BIOMEDICAL NAMED ENTITY–TERM RELATIONS

机译：生物医学命名的实体-术语关系的重新评估

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摘要

Text mining can support the interpretation of the enormous quantity of textual data produced in biomedical field. Recent developments in biomedical text mining include advances in the reliability of the recognition of named entities (NEs) such as specific genes and proteins, as well as movement toward richer representations of the associations of NEs. We argue that this shift in representation should be accompanied by the adoption of a more detailed model of the relations holding between NEs and other relevant domain terms. As a step toward this goal, we study NE–term relations with the aim of defining a detailed, broadly applicable set of relation types based on accepted domain standard concepts for use in corpus annotation and domain information extraction approaches.
机译：文本挖掘可以支持对生物医学领域产生的大量文本数据的解释。生物医学文本挖掘的最新发展包括识别诸如特定基因和蛋白质之类的命名实体（NE）的可靠性方面的进步，以及向NE关联的更丰富表示的发展。我们认为，代表制的这种转变应伴随着采用更详细的模型来描述网元与其他相关领域术语之间的关系。作为朝着这个目标迈出的一步，我们研究NE-term关系，目的是基于用于语料库注释和域信息提取方法的公认域标准概念，定义一组详细，广泛适用的关系类型。

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  • 作者

    TOMOKO OHTA; SAMPO PYYSALO; JIN-DONG KIM; JUNICHI TSUJII;

  • 作者单位

    TOMOKO OHTA Department of Computer Science, University of Tokyo, Tokyo, Japanokap.@is.s.u-tokyo.ac.jp SAMPO PYYSALO Department of Computer Science, University of Tokyo, Tokyo, Japansmp@is.s.u-tokyo.ac.jp JIN-DONG KIM Current affiliation: Database Center for Life Science, Tokyo, Japan.Department of Computer Science, University of Tokyo, Tokyo, Japanjdkim@is.s.u-tokyo.ac.jp JUN'ICHI TSUJII Department of Computer Science, University of Tokyo, Tokyo, JapanSchool of Computer Science, University of Manchester, Manchester, UKNational Centre for Text Mining, University of Manchester, Manchester, UKtsujii@is.s.u-tokyo.ac.jp;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 关键词

    Text mining; information extraction; relation representation; event representation.;

    机译：文本挖掘;信息提取;关系表示;事件表示。;

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