摘要
[目的／意义]探索领域知识发展过程中的聚类演化问题有助于揭示知识聚类的特征和规律，对于掌握知识生长演进过程中关联知识的聚集具有重要意义。[方法／过程]以复杂网络的思想为基础，基于标签邻接关系的发生值构建时间序列领域知识网络。即依据网络模体的理论，采用网络聚类系数的分析方法，对领域知识网络进行动态跟踪与分析；结合网络密度、特征路径长度、节点度值、封闭三元组等指标，从随机因素、度相关性、邻近关联3个方面对领域知识发展过程中的聚类演化现象进行分析。[结果／结论]研究结果表明：①领域知识在发展进程中始终保持较高的聚类性；②领域知识的聚类性同时包含随机性与结构性（非随机性）两方面因素；③领域知识聚类的动态状态在小世界网络和无标度网络之间摇摆演化；④领域知识的聚类状态在网络全局和局部节点之间表现出一定的差异性。
[Purpose/significance] Exploring the clustering evolution in the process of domain knowledge development can help to reveal the characteristics and rules of knowledge clustering, this is great significance to master the clustering rules of correlation knowledge in the development and evolution process. [ Method/process ] Based on the idea of complex network, this paper constructed the time series domain knowledge networks in accordance with the occurred-value of tags adjacency relation. That is, according to the network motif theory, this paper dynamically tracked and analyzed the domain knowledge networks by the analysis method of network clustering coefficient. Then, by combining with the network density, the characteristic path length, the node degree value, the triadic closure and other indicators, this article analyzed the clustering evolution in the process of domain knowledge development from random factors, degree correlation, and adjacent correlation. [ Result/conclusion] The results show： （1）Domain knowledge in the development process always keeps a higher clustering. （2）The clustering of domain knowledge includes both randomness and structuration （ non-ran- domness）. （3）The dynamic status of domain knowledge clustering evolves between small-world network and scale-free network waveringly. （4）The clustering status of domain knowledge shows a certain difference between the whole network and local nodes.
作者
安宁
滕广青
白淑春
毕强
韩尚轩
An Ning;Teng Guangqing;Bai Shuchun;Bi Qiang;Han Shangxuan(School of Information Science and Technology, Northeast Normal University, Changchun 130117;Library of Jilin University, Changchun 130012;School of Management, Jilin University, Changchun 130022)
出处
《图书情报工作》
CSSCI
北大核心
2018年第10期85-93,共9页
Library and Information Service
基金
国家自然科学基金面上项目“基于网络结构演化的Folksonomy模式中社群知识组织与知识涌现研究”(项目编号:71473035)研究成果之一
关键词
领域知识
知识网络
知识聚类
聚类系数
domain knowledge knowledge network knowledge clustering clustering coefficient
