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从生物打印文献中提取基于人工智能的知识,以识别技术趋势

Amedeo Franco Bonatti¹, Filippo Chiarello², Giovanni Vozzi¹

¹Department of Information Engineering and Research Center "Enrico Piaggio,", Systems, Territory and Construction Engineering, University of Pisa, Pisa, Italy.

3D printing and additive manufacturing

|October 3, 2024

概括

自动化自然语言处理 (NLP) 模型分析生物打印文献以提取关键词,加速制造技术,材料和应用方面的研究.

科学领域:

生物技术是生物技术.
材料科学材料科学材料科学
计算生物学计算生物学

背景情况:

生物打印文献的快速增长需要用于全面分析的先进工具.
现有的方法很难跟上日益增长的科学出版物量.
标准化命名法和确定生物打印研究的趋势是具有挑战性的.

研究的目的:

开发一个自动化关键字注释模型,用于生物打印文献分析.
利用自然语言处理 (NLP) 技术来提取关键信息.
加速新生物打印制造技术和材料的开发.

主要方法:

开发了一个组合模型,将FastText嵌入和支持矢量机 (SVM) 分类结合起来.
该模型使用生物打印摘要和作者关键词进行训练.
为了提高分类性能,采用了两步优化程序.

主要成果:

该模型成功地将关键词注释成以下类别:制造技术,材料或应用.
创建了一个关于生物打印领域的全面词典.
对技术趋势和制造-材料-应用关系的洞察力得到了提取.

结论:

拟议的NLP模型为分析生物打印科学文献提供了一个自动化解决方案.
这种方法促进了文献分析,命名标准化和趋势识别.
该模型作为在生物打印领域更复杂的自动化分析的基础.

关键词:

自动作者关键字注释.生物打印是一种生物打印技术.文献分析文献分析自然语言处理自然语言处理.

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