遗传(遗传算法)
机制(生物学)
变化(天文学)
领域(数学)
基因
干细胞
进化生物学
计算生物学
生物
认识论
遗传学
哲学
物理
数学
天体物理学
纯数学
作者
Haiyun Xu,Ming Ma,Liang Chen,Chao Wang,LO Mallasiy Muhayil Asir
标识
DOI:10.1177/01655515251330617
摘要
This study explores the key factors and internal driving forces of knowledge creation by constructing a research framework for the evolution of knowledge genes. The evolutionary mechanism of scientific topics is examined through the inheritance and variation characteristics of knowledge genes. Subject–predicate–object triples are used to identify knowledge gene topics, which are further categorised into four types based on their stability and variation features. A knowledge gene evolution path is then developed using content similarity and inheritance across adjacent time slices. Multidimensional feature analysis is applied to explore the inheritance and variation dynamics of these knowledge genes. A case study in the hematopoietic stem cells field, supported by literature validation and expert consultation, demonstrates the effectiveness of this method in enhancing the understanding of the knowledge innovation mechanism.
科研通智能强力驱动
Strongly Powered by AbleSci AI