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Leveraging knowledge sources for detecting self-reports of particular health issues on social media

机译:利用知识来源,用于检测社交媒体上特别健康问题的自我报告

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This paper investigates incorporating quality knowledge sources developed by experts for the medical domain as well as syntactic information for classification of tweets into four different health oriented categories. We claim that resources such as the MeSH hierarchy and currently available parse information are effective extensions of moderately sized training datasets for various fine-grained tweet classification tasks of self-reported health issues.
机译:本文调查了由医疗领域专家开发的质量知识来源以及句法信息,用于分类为四种不同的健康导向类别。 我们声称诸如网格层次结构和当前可用的解析信息的资源是用于自我报告的健康问题的各种细粒度推文分类任务的中等大小训练数据集的有效扩展。

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