基于数字人文的中国古代科技文献目录综述的知识挖掘与图形可视化

IF 3.4 3区 管理学 0 INFORMATION SCIENCE & LIBRARY SCIENCE
Xiang Zheng, Mingjie Li, Ze Wan, Yan Zhang
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引用次数: 0

摘要

目的本研究旨在提取中国古代科技文献文献目录提要(STDBS)中的知识,并全面系统地提供知识图谱(KG)。通过呈现内容、学科和作者之间的关系,本研究旨在为中国古代科技文献的知识发现提供服务。设计/方法论/方法本研究编制了中国古代STDBS,并设计了一个知识挖掘和图形可视化框架。作者定义了摘要的实体、属性和关系,用于知识表示,使用深度学习技术(如BERT-BiLSTM-CRF模型和规则)进行知识提取,统一实体表示进行知识融合,并使用Neo4j和其他可视化技术进行KG构建和应用。本研究以可视化图形的形式呈现了中国古代农业科技知识的产生、分布和演变。发现知识挖掘和图形可视化框架是可行和有效的。BERT-BiLSTM-CRF模型具有领域适应性和准确性。中国古代农业科技文献的知识生成具有鲜明的时代特征。知识分布不均且集中,主要集中在C1种植与栽培、C2蚕、C3桑树与水利。知识进化是明显的,分化与整合并存。原创性/价值本研究首次直观地呈现了中国古代STDBS的知识内涵和联想。它解决了中国古代STDBS缺乏深入的知识挖掘和内涵可视化的问题。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Knowledge mining and graph visualization of ancient Chinese scientific and technological documents bibliographic summaries based on digital humanities
PurposeThis study aims to extract knowledge of ancient Chinese scientific and technological documents bibliographic summaries (STDBS) and provide the knowledge graph (KG) comprehensively and systematically. By presenting the relationship among content, discipline, and author, this study focuses on providing services for knowledge discovery of ancient Chinese scientific and technological documents.Design/methodology/approachThis study compiles ancient Chinese STDBS and designs a knowledge mining and graph visualization framework. The authors define the summaries' entities, attributes, and relationships for knowledge representation, use deep learning techniques such as BERT-BiLSTM-CRF models and rules for knowledge extraction, unify the representation of entities for knowledge fusion, and use Neo4j and other visualization techniques for KG construction and application. This study presents the generation, distribution, and evolution of ancient Chinese agricultural scientific and technological knowledge in visualization graphs.FindingsThe knowledge mining and graph visualization framework is feasible and effective. The BERT-BiLSTM-CRF model has domain adaptability and accuracy. The knowledge generation of ancient Chinese agricultural scientific and technological documents has distinctive time features. The knowledge distribution is uneven and concentrated, mainly concentrated on C1-Planting and cultivation, C2-Silkworm, and C3-Mulberry and water conservancy. The knowledge evolution is apparent, and differentiation and integration coexist.Originality/valueThis study is the first to visually present the knowledge connotation and association of ancient Chinese STDBS. It solves the problems of the lack of in-depth knowledge mining and connotation visualization of ancient Chinese STDBS.
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来源期刊
Library Hi Tech
Library Hi Tech INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
8.30
自引率
44.10%
发文量
97
期刊介绍: ■Integrated library systems ■Networking ■Strategic planning ■Policy implementation across entire institutions ■Security ■Automation systems ■The role of consortia ■Resource access initiatives ■Architecture and technology ■Electronic publishing ■Library technology in specific countries ■User perspectives on technology ■How technology can help disabled library users ■Library-related web sites
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