PubMed Author-assigned Keyword Extraction (PubMedAKE) Benchmark.

Proceedings of the ... ACM International Conference on Information & Knowledge Management. ACM International Conference on Information and Knowledge Management Pub Date : 2022-10-01 Epub Date: 2022-10-17 DOI:10.1145/3511808.3557675

Jiasheng Sheng, Zelalem Gero, Joyce C Ho

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引用次数: 1

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.

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PubMed作者指定关键字提取(PubMedAKE)基准。

随着生物医学论文的不断丰富，提高关键词搜索结果的准确性对于确保研究的可重复性至关重要。然而，由于存在较为模糊的关键词和缺乏全面的基准，生物医学论文的关键词提取非常困难。PubMedAKE是一个作者指定的关键字提取数据集，其中包含来自PubMed开放存取子集数据库的超过843,269篇文章的标题、摘要和关键字。这个数据集在Zenodo上公开可用，是最大的关键字提取基准，有足够的样本来训练神经网络。使用最先进的基线方法的实验结果说明了开发生物医学文献自动关键字提取方法的必要性。

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Proceedings of the ... ACM International Conference on Information & Knowledge Management. ACM International Conference on Information and Knowledge Management

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