整合生物医学出版物与现有元数据

Nikolay Nikolov, P. Stoehr
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引用次数: 1

摘要

目前,生物医学文献在很大程度上与其元数据脱节。虽然存在可自由访问的集中元数据存储库,但出版物本身却分散在大量存储库中。我们通过从网络上收集可免费访问的生物医学出版物并将其与相应的元数据集成来解决这个问题。该系统使用基于知识的算法对检索到的出版物进行标题识别,并使用编辑距离度量对检索到的标题与元数据进行模糊匹配。到目前为止,我们能够在网络上找到30万份出版物,并在从网络上收集的250份随机样本中实现了96%的准确率和近85%的召回率。
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Integrating Biomedical Publications with Existing Metadata
Currently biomedical literature is largely disconnected from its metadata. While there are freely accessible centralised metadata repositories the publications themselves are split among a large number of repositories. We address this problem by harvesting freely accessible biomedical publications from the Web and integrating them with the corresponding metadata. The system involves title recognition applied on the harvested publications using knowledge-based algorithm and a fuzzy match between the extracted title and the metadata records using edit distance metric. So far we were able to locate +300.000 publications on the Web and achieve +96% precision and nearly 85% recall on a random sample of 250 documents harvested from the Web.
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