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Word add-in for ontology recognition: semantic enrichment of scientific literature

机译:用于本体识别的单词插件:科学文献的语义丰富

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Background In the current era of scientific research, efficient communication of information is paramount. As such, the nature of scholarly and scientific communication is changing; cyberinfrastructure is now absolutely necessary and new media are allowing information and knowledge to be more interactive and immediate. One approach to making knowledge more accessible is the addition of machine-readable semantic data to scholarly articles. Results The Word add-in presented here will assist authors in this effort by automatically recognizing and highlighting words or phrases that are likely information-rich, allowing authors to associate semantic data with those words or phrases, and to embed that data in the document as XML. The add-in and source code are publicly available at http://www.codeplex.com/UCSDBioLit . Conclusions The Word add-in for ontology term recognition makes it possible for an author to add semantic data to a document as it is being written and it encodes these data using XML tags that are effectively a standard in life sciences literature. Allowing authors to mark-up their own work will help increase the amount and quality of machine-readable literature metadata.
机译:背景技术在当前的科学研究时代,有效的信息交流至关重要。因此,学术和科学传播的性质正在发生变化。网络基础设施现在是绝对必要的,新媒体正在使信息和知识变得更具交互性和即时性。一种使知识更易于访问的方法是在学术文章中添加机器可读的语义数据。结果此处显示的Word加载项将自动识别并突出显示可能包含丰富信息的单词或短语,从而使作者能够将语义数据与这些单词或短语相关联,并将这些数据嵌入文档中,从而帮助作者进行这项工作。 XML。加载项和源代码可从http://www.codeplex.com/UCSDBioLit上公开获得。结论用于本体术语识别的Word加载项使作者可以在文档编写时将语义数据添加到文档中,并使用XML标记对这些数据进行编码,而XML标签实际上是生命科学文献中的标准。允许作者标记自己的作品将有助于提高机器可读文学元数据的数量和质量。

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