文章采用社群发现算法对领域知识网络巨分支内部的群落结构进行识别与提取，通过知识群落组成率、输出率以及群落间传承强度的计算与分析，对知识群落的演变模式与知识传承特征进行时间序列的动态跟踪与分析。研究结果表明，领域知识网络在发展演变过程中更多地处于非连通状态；领域知识发展越成熟群落之间的知识交叉融合越频繁；交叉融合性的知识传承多发生在巨分支内部的知识群落之间。

The present research uses community discovery algorithm to identify and extract the community structure inside the giant branches of domain knowledge networks. Through the calculation and analysis on inscape of knowledge communities, export of knowledge communities and lineage between communities, the time series dynamic tracking and analysis on evolution pattern and knowledge lineage characteristics of knowledge communities are carried out. The research results show that the domain knowledge networks are more non-connected in the process of evolution; the more mature the domain knowledge develops, the more frequently the knowledge cross-fusion between communities; the cross-fusion knowledge lineage mostly occurs between the knowledge communities within the giant branch.