基于BERT语言模型的电催化材料相关文献信息提取与分析

Extraction and Analysis of Electrocatalytic Material Literature Information Based on the BERT Language Model

开发了自动化文献数据提取和分析管道,该管道能够自动识别和提取文献中的关键实体和关系,包括催化剂名称、所催化的反应、催化性能等信息.利用自然语言处理(NLP)技术,从文献中自动提取电催化材料的性能数据并进行分析,为研究人员全面准确地总结前人研究成果,为开展更有创新性和更可能产生突破的研究提供重要参考信息.

The article developed an automated literature data extraction and analysis pipeline,which can automatically identify and extract key entities and relationships from the literature,including catalyst names,catalyzed reactions,catalytic performance,and other information.By utilizing Natural Language Processing(NLP)technology,it automatically extracts performance data of electro-catalytic materials from the literature and establishes a database,providing researchers with comprehensive and accurate summaries of previous research.This serves as a crucial reference for conducting more innovative and potentially breakthrough research.