论文部分内容阅读
【目的】对关联开放数据(LOD)进行结构特征分析,利用分析结果指导关联数据的组织实践。【方法】通过度分布、平均路径长度、聚类系数等指标描述LOD网络结构,对比复杂网络理论中的两个基本性质:无标度特性和小世界效应。【结果】LOD整体网络结构具有近似无标度网络的幂率分布特征,图书馆学、情报学领域子网具有相对均匀的指数分布特征,两网同时具有短平均路径长度和高聚类系数的小世界效应。【局限】缺乏对关键节点的多权重赋值。【结论】LOD的小世界特性能优化检索效率,而无标度特性会降低整个网络的稳定性。
【Objective】 The structural open-ended data (LOD) was analyzed for its structural features, and the results of the analysis were used to guide the organization and practice of related data. 【Method】 The paper describes the LOD network structure by the index of degree distribution, average path length and clustering coefficient, and compares the two basic properties in complex network theory: scale-free property and small-world effect. 【Result】 The results show that the overall LOD structure has the power-density distribution characteristics of scale-free network, and the sub-networks of library science and intelligence science have relatively uniform exponential distribution. Both networks have short average path length and high clustering coefficient Small world effect. Limitations Lack of multiple weight assignments to critical nodes. 【Conclusion】 LOD’s small-world features can optimize retrieval efficiency, while scale-free features reduce the stability of the entire network.