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Unsupervised Aspect Term Extraction in Online Drugs Reviews

机译:在线药物中的无监督方面的术语提取评论

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Aspect mining in drugs reviews has focused on extracting relevant information such as adverse reactions, efficacy of a drug, symptoms and conditions of patients. In our work, a new unsupervised and knowledge-based method is proposed for extracting aspects in drug reviews. The proposed solution is based on linguistic features, more specifically dependency paths in the syntactic tree of a review. The quality of the dependency path rules was investigated in a number of experiments in review corpora associated to three different diseases. Promising results were achieved compared to previous work.
机译:探讨药物审查的貌化审查已经专注于提取相关信息,如不良反应,药物疗效,患者的症状和病症。在我们的工作中,提出了一种新的无监督和基于知识的方法,以提取药物评论中的方面。该提出的解决方案基于语言特征,更具体地说是审查的句法树中的依赖路径。在审查与三种不同疾病相关的综述中的一项实验中研究了依赖路径规则的质量。与以前的工作相比,实现了有希望的结果。

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