关联驱动的领域知识群落生长

发布时间：2018-10-07 19:11

【摘要】：知识的发展演化一直是图书情报学界重点关注的主题。随着复杂网络理论的复兴,以网络思维探索知识发展过程中结构关系的演化成为学术界的共识。本文以知识间关联关系为基础,对社会化标注模式下Folksonomy知识组织模式中领域知识群落的生长展开研究。基于关联频度提取层次网络,利用k—丛和派系识别知识网络中的松散型与紧密型领域知识群落,从频度、关联、数量、规模、时序多个维度进行交叉复现分析。研究结果表明,领域知识群落的基本生长路径为"关联关系→松散群落→紧密群落";知识间关联关系的增长是领域知识群落生长过程中数量繁衍和规模扩容的保障;关联关系频度和数量的积累是领域知识群落生长过程中核心凝聚的过滤器。知识群落生长模式与规律的揭示,有助于从知识间的互促互扰关系方面拓展领域知识组织视野并把握知识发展脉络。但本研究在维度的划分粒度方面还有待进一步加强。图3。表4。参考文献36。
[Abstract]:The development and evolution of knowledge has always been the focus of attention in the field of library and information science. With the revival of complex network theory, it has become a consensus in academic circles to explore the evolution of structural relations in the process of knowledge development through network thinking. Based on the relationship between knowledge, this paper studies the growth of domain knowledge community in Folksonomy knowledge organization model under socialized tagging model. Based on the hierarchical network of association frequency, using k-cluster and factional to identify the loose and tight domain knowledge communities in the knowledge network, the cross-reappearance analysis is carried out from frequency, association, quantity, scale and time series. The results show that the basic growth path of domain-knowledge community is "closely related community", and the growth of knowledge association relationship is the guarantee of quantity multiplication and scale expansion in the growth process of domain knowledge community. The accumulation of frequency and quantity of association relation is the filter of core aggregation in the growth of domain knowledge community. The discovery of the growth pattern and law of knowledge community is helpful to expand the field of knowledge organization vision and grasp the development of knowledge from the aspect of mutual promotion and disturbance between knowledge. However, the granularity of dimensionality still needs to be further strengthened. Figure 3. Table 4. 36 refs.
【作者单位】：东北师范大学计算机科学与信息技术学院;
【基金】：国家自然科学基金项目“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”(编号:71473035) 教育部人文社会科学研究规划基金项目“基于后结构主义网络分析的Folksonomy模式中社群知识非线性自组织研究”(编号:14YJA870010)的研究成果之一~~
【分类号】：G302;O157.5

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