Consumer Healthcare Question Summarization Dataset and Benchmark
Analysis
This paper addresses the challenge of understanding consumer health questions online by introducing a new dataset, CHQ-Sum, for question summarization. This is important because consumers often use overly descriptive language, making it difficult for natural language understanding systems to extract key information. The dataset provides a valuable resource for developing more efficient summarization systems in the healthcare domain, which can improve access to and understanding of health information.
Key Takeaways
- •Introduces a new dataset (CHQ-Sum) for consumer healthcare question summarization.
- •Addresses the challenge of understanding consumer health questions with complex language.
- •Provides a benchmark for evaluating summarization models in the healthcare domain.
Reference
“The paper introduces a new dataset, CHQ-Sum, that contains 1507 domain-expert annotated consumer health questions and corresponding summaries.”