论文标题
Wikiumls：通过跨语性神经排名对齐Wikipedia
WikiUMLS: Aligning UMLS to Wikipedia via Cross-lingual Neural Ranking
论文作者
论文摘要
我们介绍了将统一的医学语言系统（UMLS）与Wikipedia保持一致的工作，以促进两种资源的手动对齐。我们提出了一个跨语性的神经重新疗法模型，以将UMLS概念与Wikipedia页面相匹配，Wikipedia页面可以实现72％的召回@1，比Word和Char-Level BM25的20％改善了20％，从而使手动对齐能够以最少的努力。我们发布了我们的资源，包括700k UMLS概念的排名Wikipedia页面，以及Wikiumls，这是一个用于培训和评估UMLS和Wikipedia之间的对齐模型的数据集。这将为卫生专业人员，患者和NLP系统（包括在多语言环境中）提供更容易获得Wikipedia的访问。
We present our work on aligning the Unified Medical Language System (UMLS) to Wikipedia, to facilitate manual alignment of the two resources. We propose a cross-lingual neural reranking model to match a UMLS concept with a Wikipedia page, which achieves a recall@1 of 72%, a substantial improvement of 20% over word- and char-level BM25, enabling manual alignment with minimal effort. We release our resources, including ranked Wikipedia pages for 700k UMLS concepts, and WikiUMLS, a dataset for training and evaluation of alignment models between UMLS and Wikipedia. This will provide easier access to Wikipedia for health professionals, patients, and NLP systems, including in multilingual settings.
