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- W3100209521 abstract "We present a query-based biomedical information retrieval task across two vastly different genres -- newswire and research literature -- where the goal is to find the research publication that supports the primary claim made in a health-related news article. For this task, we present a new dataset of 5,034 claims from news paired with research abstracts. Our approach consists of two steps: (i) selecting the most relevant candidates from a collection of 222k research abstracts, and (ii) re-ranking this list. We compare the classical IR approach using BM25 with more recent transformer-based models. Our results show that cross-genre medical IR is a viable task, but incorporating domain-specific knowledge is crucial." @default.
- W3100209521 created "2020-11-23" @default.
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- W3100209521 date "2020-01-01" @default.
- W3100209521 modified "2023-09-26" @default.
- W3100209521 title "Querying Across Genres for Medical Claims in News" @default.
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- W3100209521 doi "https://doi.org/10.18653/v1/2020.emnlp-main.139" @default.
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