取代非生物医学概念可以改善生物医学概念的嵌入
Enock Niyonkuru1,2, Mauricio Soto Gomez3, Elena Casarighi3,4,5
1The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America.
PloS one
|May 5, 2025
概括
替换非生物医学同义词可以改善机器学习的词嵌入. 这种方法减少了噪音,提高了向量空间中生物医学概念表示的质量.
科学领域:
- 自然语言处理自然语言处理.
- 生物信息学是一种生物信息学.
- 机器学习 机器学习
背景情况:
- 嵌入式表示矢量空间中的单词,对于机器学习至关重要.
- 生物医学嵌入传统上是标准化的概念同义词.
- 非生物医学同义词替换对嵌入质量的影响还未得到充分研究.
研究的目的:
- 调查替换非生物医学同义词对嵌入质量的影响.
- 通过标准化非生物医学术语来减少嵌入式环境中的噪音.
- 提高生物医学概念表示的连贯性.
主要方法:
- 利用WordNet识别和替换非生物医学同义词.
- 在1055个生物医学概念集中应用了综合方法.
- 在1000万个PubMed摘要上使用Word2Vec生成嵌入.
主要成果:
- 非生物医学同义词替换可将平均对距离减少8%.
- 这表明集群内部的一致性有所改善,嵌入质量更高.
- 互补的方法增强了生物医学概念表示的完整性.
结论:
- 替换非生物医学同义词是改善生物医学嵌入的有价值的补充技术.
- 这种方法提供了一种切实可行的方法来减少噪音并提高嵌入质量.
- 进一步的研究将探索其适用于其他嵌入技术和下游任务的可用性.
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