知识群落演化与知识传递模式研究

Research on the Evolution of Knowledge Communities and Knowledge Transmitting Pattern

探索领域知识网络中知识群落及其演化模式,对于掌握领域知识发展过程中的知识交叉融合以及知识继承具有重要意义。基于标签邻接关系构建时间序列领域知识网络。通过社群发现算法识别领域知识网络中的知识群落。基于群落数量、群落规模、变异系数等指标,对知识群落生长路径和演化模式进行跟踪与分析。研究结果表明,大规模知识群落随着领域知识的发展逐渐涌现;小规模知识群落在演化过程中与其他知识交叉融合;大规模知识群落倾向于集中传递群落中的主要知识内容。

Exploring the knowledge community and its evolutionary pattern in the domain knowledge network is of great significance for mastering knowledge cross-convergence and knowledge inheritance in the process of domain knowledge development. Time series domain knowledge networks are constructed based on tags adjacency relationship. The community discovery algorithm is used to identify the knowledge communities in the domain knowledge networks. Based on the number of communities, the size of the communities, the variation coefficients, and other indicators, the growth path and evolution pattern of the knowledge community are tracked and analyzed. The research results show that large-scale knowledge communities gradually emerge with the development of domain knowledge; small-scale knowledge communities are intertwined with other knowledge in the evolution process; and large-scale knowledge communities tend to intensively deliver main knowledge content in the communities.