Martin Melanie J
Computer Science Department, California State University, Stanislaus, One University Circle, Turlock California, 95382, USA.
J Biomed Semantics. 2011;2 Suppl 3(Suppl 3):S5. doi: 10.1186/2041-1480-2-S3-S5. Epub 2011 Jul 14.
In this paper we present a detailed scheme for annotating medical web pages designed for health care consumers. The annotation is along two axes: first, by reliability (the extent to which the medical information on the page can be trusted), second, by the type of page (patient leaflet, commercial, link, medical article, testimonial, or support).
We analyze inter-rater agreement among three judges for each axis. Inter-rater agreement was moderate (0.77 accuracy, 0.62 F-measure, 0.49 Kappa) on the page reliability axis and good (0.81 accuracy, 0.72 F-measure, 0.73 Kappa) along the page type axis.
We have shown promising results in this study that appropriate classes of pages can be developed and used by human annotators to annotate web pages with reasonable to good agreement.
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在本文中,我们提出了一个详细的方案,用于注释面向医疗保健消费者的医学网页。注释沿着两个轴进行:第一,按可靠性(页面上医学信息可被信任的程度);第二,按页面类型(患者传单、商业、链接、医学文章、推荐或支持)。
我们分析了三位评判者在每个轴上的评分者间一致性。在页面可靠性轴上,评分者间一致性为中等(准确率0.77,F值0.62,卡帕值0.49),在页面类型轴上为良好(准确率0.81,F值0.72,卡帕值0.73)。
我们在本研究中展示了有前景的结果,即人类注释者可以开发并使用合适的页面类别,以合理到良好的一致性来注释网页。
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