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A Conceptual Model for Retrieval of Chinese Frequently Asked Questions in Healthcare

机译:医疗保健中常见问题解答的概念模型

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Frequently asked questions (FAQs) in healthcare provide general readers with both reliable and readable healthcare information. In this paper, we present a conceptual retrieval technique that serves as a supplement to enhance existing FAQ retrievers to find Chinese healthcare FAQs for each input query. By analyzing the structures and goals of Chinese healthcare FAQs, we identify three types of essential concepts in healthcare FAQs: event, condition, and aspect, as a Chinese healthcare FAQ often cares about some aspects (e.g., cause) of some events (e.g., cardiovascular disease) under some condition (e.g., patients of the periodontal disease). The proposed conceptual retrieval technique is thus named ECA (Event, Condition, and Aspect). Given healthcare FAQs annotated by the three types of concepts, ECA can measure the conceptual similarities between an input query and the FAQs. Empirical evaluation on real-world Chinese healthcare FAQs shows that the conceptual similarity information provided by ECA is helpful for an FAQ retriever to have significantly better performance in identifying relevant FAQs for input queries.
机译:医疗保健中的常见问题(常见问题解答)提供了具有可靠和可读的医疗保健信息的通用读者。在本文中,我们提出了一种概念检索技术,作为增强的补充,以增强现有的常见问题解答,为每个输入查询找到中国医疗保健常见问题解答。通过分析中国医疗保健常见问题解答的结构和目标,我们在医疗保健常见问题解答中确定了三种类型的基本概念:事件,条件和方面,作为中国医疗保健常见问题,通常关心一些事件的某些方面(例如,心血管疾病)在某些条件下(例如,牙周病患者)。因此,所提出的概念检索技术是名为ECA(事件,条件和方面)。给定医疗保健常见问题解答由三种类型的概念注释,ECA可以测量输入查询和常见问题解答之间的概念相似之词。实证对现实世界医疗保健常见问题解答的实证评估表明,ECA提供的概念相似性信息对常见问题解答牵引者有助于在识别输入查询的相关常见问题解答方面具有明显更好的性能。

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