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- W4306317384 abstract "With the ever-increasing abundance of biomedical articles, improving the accuracy of keyword search results becomes crucial for ensuring reproducible research. However, keyword extraction for biomedical articles is hard due to the existence of obscure keywords and the lack of a comprehensive benchmark. PubMedAKE is an author-assigned keyword extraction dataset that contains the title, abstract, and keywords of over 843,269 articles from the PubMed open access subset database. This dataset, publicly available on Zenodo, is the largest keyword extraction benchmark with sufficient samples to train neural networks. Experimental results using state-of-the-art baseline methods illustrate the need for developing automatic keyword extraction methods for biomedical literature." @default.
- W4306317384 created "2022-10-16" @default.
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- W4306317384 date "2022-10-17" @default.
- W4306317384 modified "2023-09-25" @default.
- W4306317384 title "PubMed Author-assigned Keyword Extraction (PubMedAKE) Benchmark" @default.
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- W4306317384 doi "https://doi.org/10.1145/3511808.3557675" @default.
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