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CHQ-Summ: A Dataset for Consumer Healthcare Question Summarization

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arxiv 2206.06581 v2 pith:VP4YXMVC submitted 2022-06-14 cs.CL

classification cs.CL
keywords datasetconsumerinformationquestionsaddresschq-summconsumershealth
verification ladder T0 review T1 audit T2 compute T3 formal
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The quest for seeking health information has swamped the web with consumers' health-related questions. Generally, consumers use overly descriptive and peripheral information to express their medical condition or other healthcare needs, contributing to the challenges of natural language understanding. One way to address this challenge is to summarize the questions and distill the key information of the original question. To address this issue, we introduce a new dataset, CHQ-Summ that contains 1507 domain-expert annotated consumer health questions and corresponding summaries. The dataset is derived from the community question-answering forum and therefore provides a valuable resource for understanding consumer health-related posts on social media. We benchmark the dataset on multiple state-of-the-art summarization models to show the effectiveness of the dataset.

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