LOV词表特征及网络结构分析

Analysis of LOV Vocabulary Features and Network Structure

【目的/意义】关联开放词汇表(LOV)作为关联开放数据云(LOD)的重要组成部分,旨在提供对LOD中所使用词表的便捷访问,对LOV词表特征与网络结构进行探讨,一定程度上揭示了关联数据的演化和动态规律。【方法/过程】本文从LOV数据网络的基本特征、结构特征两个角度入手,借助数理统计与复杂网络分析方法,对从LOV官网收集到的数据进行深入分析。【结果/结论】了解词表基本特征的分布规律、集中趋势、离散程度以及词表的网络结构特征,并验证LOV网络结构遵循了复杂网络中的无标度特性和小世界理论。【创新/局限】从度量学的角度来观察LOV网络,可为全面了解LOV词表特征和结构,在映射和使用重要词表时提供参考。由于本文使用的是静态数据,因此未来可收集动态数据,对词表网络演化过程进行更进一步的探析,从而从更深层次揭示LOV网络的生长模式与规律。

【Purpose/significance】Linked Open Vocabulary(LOV) is an important part of Linked Open Data Cloud(LOD), which aims to provide easy access to the vocabulary used in LOD. To explore the characteristics of LOV vocabulary and network structure, which reveals the evolution and dynamic law of linked data.【Method/process】This paper starts from the two aspects of the basic characteristics and structural characteristics of the LOV network. Through the mathematical statistics and complex network analysis methods, the data collected from the LOV official website is analyzed in depth.【Result/conclusion】Understand the distribution law, concentration trend, degree of dispersion, and network structure characteristics of vocabulary, and verify that the LOV network structure follows the scale-free characteristics and small world theory in complex networks.【Innovation/limitation】Observing the LOV network from a metrics perspective provides a comprehensive understanding of the LOV vocabulary features and structure, and provides a reference for mapping and using important vocabularies. Because this paper uses static data, we can collect dynamic data in the future to further explore the evolution process of thesaurus network, so as to reveal the growth pattern and law of LOV network from a deeper level.