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Accessing bioscience images from abstract sentences

机译:从抽象句子中获取生物科学图像

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摘要

Images (e.g., figures) are important experimental results that are typically reported in bioscience full-text articles. Biologists need to access images to validate research facts and to formulate or to test novel research hypotheses. On the other hand, biologists live in an age of information explosion. As thousands of biomedical articles are published every day, systems that help biologists efficiently access images in literature would greatly facilitate biomedical research. We hypothesize that much of image content reported in a full-text article can be summarized by the sentences in the abstract of the article. In our study, more than one hundred biologists had tested this hypothesis and more than 40 biologists had evaluated a novel user-interface BioEx that allows biologists to access images directly from abstract sentences. Our results show that 87.8% biologists were in favor of BioEx over two other baseline user-interfaces. We further developed systems that explored hierarchical clustering algorithms to automatically identify abstract sentences that summarize the images. One of the systems achieves a precision of 100% that corresponds to a recall of 4.6%.
机译:图像(例如数字)是重要的实验结果,通常在生物科学全文文章中进行报道。生物学家需要访问图像以验证研究事实,并制定或检验新颖的研究假设。另一方面,生物学家生活在信息爆炸时代。每天都有成千上万的生物医学文章发表,帮助生物学家有效获取文献图像的系统将极大地促进生物医学研究。我们假设全文文章中报道的许多图像内容都可以由文章摘要中的句子来概括。在我们的研究中,一百多位生物学家对此假设进行了检验,四十多位生物学家评估了一种新颖的BioEx用户界面,该界面使生物学家可以直接从抽象句子中访问图像。我们的结果表明,与其他两个基准用户界面相比,有87.8%的生物学家赞成BioEx。我们进一步开发了探索分层聚类算法以自动识别摘要图像的抽象句子的系统。其中一种系统达到了100%的精度,相当于召回率为4.6%。

著录项

  • 来源
    《Bioinformatics》 |2006年第14期|e547-e556|共10页
  • 作者

    Hong Yu; and Minsuk Lee;

  • 作者单位

    Department of Health Sciences University of Wisconsin-MilwaukeeWisconsin;

    CEAS University of Wisconsin-MilwaukeeWisconsin;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-18 01:14:38

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