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Automatic Retrieval of Web Pages with Standards of Ethics and Trustworthiness Within a Medical Portal: What a Page Name Tells Us

机译:在医疗门户网站中自动检索具有道德和可信度标准的网页:页面名称告诉我们什么

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摘要

The ever-increasing volume of health online information, coupled with the uneven reliability and quality, may have considerable implications for the citizen. In order to address this issue, we propose to use, within a general or specialised search engine, standards for identifying the reliability of online documents. Standards used are those related to the ethics as well as trustworthiness of websites. In this research, they are detected through the URL names of Web pages by applying machine learning algorithms. According to algorithms used and to principles, our straightforward approach shows up to 93% precision and 91% recall. But a few principles remain difficult to recognize.
机译:卫生在线信息的不断增加,加上可靠性和质量的不均衡,可能会对公民产生重大影响。为了解决此问题,我们建议在一般或专门的搜索引擎中使用用于识别在线文档可靠性的标准。使用的标准是与网站的道德规范和可信度相关的标准。在这项研究中,通过应用机器学习算法通过网页的URL名称检测到它们。根据使用的算法和原则,我们直接的方法显示出高达93%的精度和91%的召回率。但是,一些原则仍然难以识别。

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