论文标题
化学专利天然语言处理的单词嵌入
Word Embeddings for Chemical Patent Natural Language Processing
论文作者
论文摘要
我们对针对已知生物医学嵌入的化学专利单词嵌入进行评估，并表明它们在外部和内部均优于后者。我们还表明，使用上下文化的嵌入可以在相对较小的黄金标准上诱导该域的合理性能的预测模型。
We evaluate chemical patent word embeddings against known biomedical embeddings and show that they outperform the latter extrinsically and intrinsically. We also show that using contextualized embeddings can induce predictive models of reasonable performance for this domain over a relatively small gold standard.
